NeurIPS 2023 Thursday 12/14

Timezone: America/Chicago

Full Schedule Sun 12/10 Mon 12/11 Tue 12/12 Wed 12/13 Thu 12/14 Fri 12/15 Sat 12/16

Registration Desk

7:30 AM - 6:00 PM

Invited Talk

Systems for Foundation Models, and Foundation Models for Systems.

Christopher Ré

8:30 AM - 9:20 AM

I'm a simple creature. I fell in love with foundation models (FMs) because they radically improved data systems that I had been trying to build for a decade–and they are just awesome! This talk starts with my perspective about how FMs change the systems we build, focusing on what I call "death by a thousand cuts" problems. Roughly, these are problems in which each individual task looks easy, but the sheer variety and breadth of tasks make them hard.

The bulk of the talk is about understanding how to efficiently build foundation models. We describe trends in hardware accelerators from a perhaps unexpected viewpoint: database systems research. Databases have worried about optimizing IO – reads and writes within the memory hierarchy – since the 80s. In fact, optimizing IO led to Flash Attention for Transformers.

But are there more efficient architectures for foundation models than the Transformer? Maybe! I'll describe a new class of architectures based on classical signal processing, exemplified by S4. These new architectures: are asymptotically more efficient than Transformers for long sequences, have achieved state-of-the-art quality on benchmarks like long range arena, and have been applied to images, text, DNA, audio, video. S4 will allow us to make mathematically precise connections to RNNs and CNNs. I’ll also describe new twists, such as, long filters, data-dependent convolutions, and gating, that power many of these amazing recent architectures including RWKV, S5, Mega, Hyena, and RetNet, and recent work to understand their fundamental limitations to hopefully make even more awesome foundation models!

A github containing material from is under construction at https://github.com/HazyResearch/aisys-building-blocks. Please feel free to add to it!

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Speaker Bio

Christopher (Chris) Re is an associate professor in the Department of Computer Science at Stanford University. He is in the Stanford AI Lab and is affiliated with the Machine Learning Group and the Center for Research on Foundation Models. His recent work is to understand how software and hardware systems will change because of machine learning along with a continuing, petulant drive to work on math problems. Research from his group has been incorporated into scientific and humanitarian efforts, such as the fight against human trafficking, along with products from technology and companies including Apple, Google, YouTube, and more. He has also cofounded companies, including Snorkel, SambaNova, and Together, and a venture firm, called Factory. His family still brags that he received the MacArthur Foundation Fellowship, but his closest friends are confident that it was a mistake. His research contributions have spanned database theory, database systems, and machine learning, and his work has won best paper at a premier venue in each area, respectively, at PODS 2012, SIGMOD 2014, and ICML 2016. Due to great collaborators, he received the NeurIPS 2020 test-of-time award and the PODS 2022 test-of-time award. Due to great students, he received best paper at MIDL 2022, best paper runner up at ICLR22 and ICML22, and best student-paper runner up at UAI22.

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Oral

Oral 5A GNNs/Invariance

10:00 AM - 10:45 AM

3 Events in this session

Going beyond persistent homology using persistent homology

Johanna Immonen · Amauri Souza · Vikas Garg

Clifford Group Equivariant Neural Networks

David Ruhe · Johannes Brandstetter · Patrick Forré

Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis

Junfeng Fang · Wei Liu · Yuan Gao · Zemin Liu · An Zhang · Xiang Wang · Xiangnan He

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Oral

Oral 5D Vision

10:00 AM - 10:45 AM

3 Events in this session

Visual Instruction Tuning

Haotian Liu · Chunyuan Li · Qingyang Wu · Yong Jae Lee

EgoEnv: Human-centric environment representations from egocentric video

Tushar Nagarajan · Santhosh Kumar Ramakrishnan · Ruta Desai · James Hillis · Kristen Grauman

DataComp: In search of the next generation of multimodal datasets

Samir Yitzhak Gadre · Gabriel Ilharco · Alex Fang · Jonathan Hayase · Georgios Smyrnis · Thao Nguyen · Ryan Marten · Mitchell Wortsman · Dhruba Ghosh · Jieyu Zhang · Eyal Orgad · Rahim Entezari · Giannis Daras · Sarah Pratt · Vivek Ramanujan · Yonatan Bitton · Kalyani Marathe · Stephen Mussmann · Richard Vencu · Mehdi Cherti · Ranjay Krishna · Pang Wei Koh · Olga Saukh · Alexander Ratner · Shuran Song · Hannaneh Hajishirzi · Ali Farhadi · Romain Beaumont · Sewoong Oh · Alex Dimakis · Jenia Jitsev · Yair Carmon · Vaishaal Shankar · Ludwig Schmidt

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Oral

Oral 5C Probability/Sampling

10:00 AM - 10:45 AM

3 Events in this session

Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent

Jihao Andreas Lin · Javier Antorán · Shreyas Padhy · David Janz · José Miguel Hernández-Lobato · Alexander Terenin

A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods

Veit David Wild · Sahra Ghalebikesabi · Dino Sejdinovic · Jeremias Knoblauch

Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method

Constantine Caramanis · Dimitris Fotakis · Alkis Kalavasis · Vasilis Kontonis · Christos Tzamos

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Oral

Oral 5B Privacy/Fairness

10:00 AM - 10:45 AM

3 Events in this session

Students Parrot Their Teachers: Membership Inference on Model Distillation

Matthew Jagielski · Milad Nasr · Katherine Lee · Christopher A. Choquette-Choo · Nicholas Carlini · Florian Tramer

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

Samuel Dooley · Rhea Sukthanker · John Dickerson · Colin White · Frank Hutter · Micah Goldblum

Ethical Considerations for Responsible Data Curation

Jerone Andrews · Dora Zhao · William Thong · Apostolos Modas · Orestis Papakyriakopoulos · Alice Xiang

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Poster

Poster Session 5

10:45 AM - 12:45 PM

600 Events in this session

SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data

BANG AN · Xun Zhou · Xun Zhou · YONGJIAN ZHONG · Tianbao Yang

Learning to Group Auxiliary Datasets for Molecule

Tinglin Huang · Ziniu Hu · Rex Ying

A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design

Fang Wu · Stan Z. Li

DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening

Bowen Gao · Bo Qiang · Haichuan Tan · Yinjun Jia · Minsi Ren · Minsi Lu · Jingjing Liu · Wei-Ying Ma · Yanyan Lan

Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules

ZHIYUAN LIU · Yaorui Shi · An Zhang · Enzhi Zhang · Kenji Kawaguchi · Xiang Wang · Tat-Seng Chua

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration

Haitao Lin · Yufei Huang · Odin Zhang · Yunfan Liu · Lirong Wu · Siyuan Li · Zhiyuan Chen · Stan Z. Li

Learning Invariant Molecular Representation in Latent Discrete Space

Xiang Zhuang · Qiang Zhang · Keyan Ding · Yatao Bian · Xiao Wang · Jingsong Lv · Hongyang Chen · Huajun Chen

Prefix-Tree Decoding for Predicting Mass Spectra from Molecules

Samuel Goldman · John Bradshaw · Jiayi Xin · Connor Coley

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

Haiyang Yu · Meng Liu · Youzhi Luo · Alex Strasser · Xiaofeng Qian · Xiaoning Qian · Shuiwang Ji

CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoders

Anthony Fuller · Koreen Millard · James Green

NeRF Revisited: Fixing Quadrature Instability in Volume Rendering

Mikaela Angelina Uy · Kiyohiro Nakayama · Guandao Yang · Rahul Thomas · Leonidas Guibas · Ke Li

Self-Supervised Motion Magnification by Backpropagating Through Optical Flow

Zhaoying Pan · Daniel Geng · Andrew Owens

Point Cloud Completion with Pretrained Text-to-Image Diffusion Models

Yoni Kasten · Ohad Rahamim · Gal Chechik

Inferring Hybrid Neural Fluid Fields from Videos

Hong-Xing Yu · Yang Zheng · Yuan Gao · Yitong Deng · Bo Zhu · Jiajun Wu

UE4-NeRF:Neural Radiance Field for Real-Time Rendering of Large-Scale Scene

Jiaming Gu · Minchao Jiang · Hongsheng Li · Xiaoyuan Lu · Guangming Zhu · Syed Afaq Ali Shah · Liang Zhang · Mohammed Bennamoun

CAST: Cross-Attention in Space and Time for Video Action Recognition

Dongho Lee · Jongseo Lee · Jinwoo Choi

Unleash the Potential of Image Branch for Cross-modal 3D Object Detection

Yifan Zhang · Qijian Zhang · Junhui Hou · Yixuan Yuan · Guoliang Xing

POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images

Antonin Vobecky · Oriane Siméoni · David Hurych · Spyridon Gidaris · Andrei Bursuc · Patrick Pérez · Josef Sivic

A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation

Qitao Zhao · Ce Zheng · Ce Zheng · Mengyuan Liu · Chen Chen

From ViT Features to Training-free Video Object Segmentation via Streaming-data Mixture Models

Roy Uziel · Or Dinari · Oren Freifeld

EgoEnv: Human-centric environment representations from egocentric video

Tushar Nagarajan · Santhosh Kumar Ramakrishnan · Ruta Desai · James Hillis · Kristen Grauman

Activity Grammars for Temporal Action Segmentation

Dayoung Gong · Joonseok Lee · Deunsol Jung · Suha Kwak · Minsu Cho

Detecting Any Human-Object Interaction Relationship: Universal HOI Detector with Spatial Prompt Learning on Foundation Models

Yichao Cao · Qingfei Tang · Xiu Su · Song Chen · Shan You · Xiaobo Lu · Chang Xu

CorresNeRF: Image Correspondence Priors for Neural Radiance Fields

Yixing Lao · Xiaogang Xu · zhipeng cai · Xihui Liu · Hengshuang Zhao

Q-DM: An Efficient Low-bit Quantized Diffusion Model

Yanjing Li · Sheng Xu · Xianbin Cao · Xiao Sun · Baochang Zhang

PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds

Hao Yang · Haiyang Wang · Di Dai · Liwei Wang

DäRF: Boosting Radiance Fields from Sparse Input Views with Monocular Depth Adaptation

Jiuhn Song · Seonghoon Park · Honggyu An · Seokju Cho · Min-Seop Kwak · Sungjin Cho · Seungryong Kim

Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery

Sarah Rastegar · Hazel Doughty · Cees Snoek

Scaling Open-Vocabulary Object Detection

Matthias Minderer · Alexey Gritsenko · Neil Houlsby

LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction

Di Liu · Anastasis Stathopoulos · Qilong Zhangli · Yunhe Gao · Dimitris Metaxas

Sensitivity in Translation Averaging

Lalit Manam · Venu Madhav Govindu

BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing

DONGXU LI · Junnan Li · Junnan Li · Steven Hoi

ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors

Xiaoxuan Ma · Stephan Kaufhold · Jiajun Su · Wentao Zhu · Jack Terwilliger · Andres Meza · Yixin Zhu · Federico Rossano · Yizhou Wang

FouriDown: Factoring Down-Sampling into Shuffling and Superposing

Qi Zhu · man zhou · Jie Huang · Naishan Zheng · Hongzhi Gao · Chongyi Li · Yuan Xu · Feng Zhao

Slot-guided Volumetric Object Radiance Fields

DI QI · Tong Yang · Xiangyu Zhang

Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision

Ayush Tewari · Tianwei Yin · George Cazenavette · Semon Rezchikov · Josh Tenenbaum · Fredo Durand · Bill Freeman · Vincent Sitzmann

CLIP4HOI: Towards Adapting CLIP for Practical Zero-Shot HOI Detection

Yunyao Mao · Jiajun Deng · Wengang Zhou · Li Li · Yao Fang · Houqiang Li

Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation

Yuan Wang · Naisong Luo · Tianzhu Zhang

CluB: Cluster Meets BEV for LiDAR-Based 3D Object Detection

Yingjie Wang · Jiajun Deng · Yuenan Hou · Yao Li · Yu Zhang · Jianmin Ji · Wanli Ouyang · Yanyong Zhang

IEBins: Iterative Elastic Bins for Monocular Depth Estimation

Shuwei Shao · Zhongcai Pei · Xingming Wu · Zhong Liu · Weihai Chen · Zhengguo Li

What Makes Good Examples for Visual In-Context Learning?

Yuanhan Zhang · Kaiyang Zhou · Ziwei Liu

Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis

Zhu Wang · Sourav Medya · Sathya Ravi

DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model

Xiuye Gu · Yin Cui · Jonathan Huang · Abdullah Rashwan · Xuan Yang · Xingyi Zhou · Golnaz Ghiasi · Weicheng Kuo · Huizhong Chen · Liang-Chieh Chen · David Ross

AutoGO: Automated Computation Graph Optimization for Neural Network Evolution

Mohammad Salameh · Keith Mills · Negar Hassanpour · Fred Han · Shuting Zhang · Wei Lu · Shangling Jui · CHUNHUA ZHOU · Fengyu Sun · Di Niu

A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence

Junyi Zhang · Charles Herrmann · Junhwa Hur · Luisa Polania Cabrera · Varun Jampani · Deqing Sun · Ming-Hsuan Yang

SPA: A Graph Spectral Alignment Perspective for Domain Adaptation

Zhiqing Xiao · Haobo Wang · Ying Jin · Lei Feng · Gang Chen · Fei Huang · Junbo Zhao

Learning Motion Refinement for Unsupervised Face Animation

Jiale Tao · Shuhang Gu · Wen Li · Lixin Duan

RegBN: Batch Normalization of Multimodal Data with Regularization

Morteza Ghahremani Boozandani · Christian Wachinger

Uncertainty-Aware Alignment Network for Cross-Domain Video-Text Retrieval

Xiaoshuai Hao · Wanqian Zhang

LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections

Muhammad Jehanzeb Mirza · Leonid Karlinsky · Wei Lin · Horst Possegger · Mateusz Kozinski · Rogerio Feris · Horst Bischof

Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism

Chengcheng Wang · Wei He · Ying Nie · Jianyuan Guo · Chuanjian Liu · Yunhe Wang · Kai Han

DynPoint: Dynamic Neural Point For View Synthesis

Kaichen Zhou · Jia-Xing Zhong · Sangyun Shin · Kai Lu · Yiyuan Yang · Andrew Markham · Niki Trigoni

Diff-Foley: Synchronized Video-to-Audio Synthesis with Latent Diffusion Models

Simian Luo · Chuanhao Yan · Chenxu Hu · Hang Zhao

Social Motion Prediction with Cognitive Hierarchies

Wentao Zhu · Jason Qin · Yuke Lou · Hang Ye · Xiaoxuan Ma · Hai Ci · Yizhou Wang

Visual Instruction Inversion: Image Editing via Image Prompting

Thao Nguyen · Yuheng Li · Utkarsh Ojha · Yong Jae Lee

LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer

Haoyu Chen · Hao Tang · Radu Timofte · Luc V Gool · Guoying Zhao

Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation

Tingliang Feng · Hao Shi · Xueyang Liu · Wei Feng · Liang Wan · Yanlin Zhou · Di Lin

Binarized Spectral Compressive Imaging

Yuanhao Cai · Yuxin Zheng · Jing Lin · Xin Yuan · Yulun Zhang · Haoqian Wang

Learning Re-sampling Methods with Parameter Attribution for Image Super-resolution

Xiaotong Luo · Yuan Xie · Yanyun Qu

Reducing Shape-Radiance Ambiguity in Radiance Fields with a Closed-Form Color Estimation Method

Qihang Fang · Qihang Fang · Yafei Song · Keqiang Li · Liefeng Bo

Visual Instruction Tuning

Haotian Liu · Chunyuan Li · Qingyang Wu · Yong Jae Lee

ARTIC3D: Learning Robust Articulated 3D Shapes from Noisy Web Image Collections

Chun-Han Yao · Amit Raj · Wei-Chih Hung · Michael Rubinstein · Yuanzhen Li · Ming-Hsuan Yang · Varun Jampani

Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection

Linyan Huang · Zhiqi Li · Chonghao Sima · Wenhai Wang · Jingdong Wang · Yu Qiao · Hongyang Li

PromptRestorer: A Prompting Image Restoration Method with Degradation Perception

Cong Wang · Jinshan Pan · Wei Wang · Jiangxin Dong · Mengzhu Wang · Yakun Ju · Junyang Chen

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

Chenyu You · Weicheng Dai · Yifei Min · Fenglin Liu · David Clifton · S. Kevin Zhou · Lawrence Staib · James Duncan

PHOTOSWAP: Personalized Subject Swapping in Images

Jing Gu · Yilin Wang · Nanxuan Zhao · Tsu-Jui Fu · Wei Xiong · Qing Liu · Zhifei Zhang · HE Zhang · Jianming Zhang · HyunJoon Jung · Xin Eric Wang

Diffusion-TTA: Test-time Adaptation of Discriminative Models via Generative Feedback

Mihir Prabhudesai · Tsung-Wei Ke · Alex Li · Deepak Pathak · Katerina Fragkiadaki

Global-correlated 3D-decoupling Transformer for Clothed Avatar Reconstruction

Zechuan Zhang · Li Sun · Zongxin Yang · Ling Chen · Yi Yang

Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition

Shuhuai Ren · Aston Zhang · Yi Zhu · Shuai Zhang · Shuai Zheng · Mu Li · Alexander Smola · Xu Sun

AD-PT: Autonomous Driving Pre-Training with Large-scale Point Cloud Dataset

Jiakang Yuan · Bo Zhang · Xiangchao Yan · Botian Shi · Tao Chen · Yikang LI · Yu Qiao

$SE(3)$ Equivariant Convolution and Transformer in Ray Space

Yinshuang Xu · Jiahui Lei · Kostas Daniilidis

Flow-Based Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection

Haibao Yu · Yingjuan Tang · Enze Xie · Jilei Mao · Ping Luo · Zaiqing Nie

Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction

Anagh Malik · Parsa Mirdehghan · Sotiris Nousias · Kyros Kutulakos · David Lindell

Toward Re-Identifying Any Animal

Bingliang Jiao · Lingqiao Liu · Liying Gao · Ruiqi Wu · Guosheng Lin · PENG WANG · Yanning Zhang

Prototypical Variational Autoencoder for 3D Few-shot Object Detection

Weiliang Tang · Biqi YANG · Xianzhi Li · Yun-Hui Liu · Pheng-Ann Heng · Chi-Wing Fu

Uncertainty Quantification via Neural Posterior Principal Components

Elias Nehme · Omer Yair · Tomer Michaeli

UniTSFace: Unified Threshold Integrated Sample-to-Sample Loss for Face Recognition

qiufu li · Xi Jia · Jiancan Zhou · Linlin Shen · Jinming Duan

Scattering Vision Transformer: Spectral Mixing Matters

Badri Patro · Vijay Agneeswaran

Video Timeline Modeling For News Story Understanding

Meng Liu · Mingda Zhang · Jialu Liu · Hanjun Dai · Ming-Hsuan Yang · Shuiwang Ji · Zheyun Feng · Boqing Gong

EV-Eye: Rethinking High-frequency Eye Tracking through the Lenses of Event Cameras

Guangrong Zhao · Yurun Yang · Jingwei Liu · Ning Chen · Yiran Shen · Hongkai Wen · Guohao Lan

ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns

Ren Li · Benoît Guillard · Benoit Guillard · Pascal Fua

LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas

Kensen Shi · Hanjun Dai · Wen-Ding Li · Kevin Ellis · Charles Sutton

Multi-Objective Intrinsic Reward Learning for Conversational Recommender Systems

Zhendong Chu · Nan Wang · Hongning Wang

Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion

Zhengyi Yang · Jiancan Wu · Zhicai Wang · Xiang Wang · Yancheng Yuan · Xiangnan He

xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data

Jing Gong · Minsheng Hao · Xingyi Cheng · Xin Zeng · Chiming Liu · Jianzhu Ma · Xuegong Zhang · Taifeng Wang · Le Song

Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning

Ronald Xie · Kuan Pang · Sai Chung · Catia Perciani · Sonya MacParland · Bo Wang · Gary Bader

Individualized Dosing Dynamics via Neural Eigen Decomposition

Stav Belogolovsky · Ido Greenberg · Danny Eytan · Shie Mannor

DDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models

Ge Zheng · Bin Yang · Jiajin Tang · Hong-Yu Zhou · Sibei Yang

C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models

Yuzhen Huang · Yuzhuo Bai · Zhihao Zhu · Junlei Zhang · Jinghan Zhang · Tangjun Su · Junteng Liu · Chuancheng Lv · Yikai Zhang · jiayi lei · Yao Fu · Maosong Sun · Junxian He

Focused Transformer: Contrastive Training for Context Scaling

Szymon Tworkowski · Konrad Staniszewski · Mikołaj Pacek · Yuhuai Wu · Henryk Michalewski · Piotr Miłoś

High-Fidelity Audio Compression with Improved RVQGAN

Rithesh Kumar · Prem Seetharaman · Alejandro Luebs · Ishaan Kumar · Kundan Kumar

Improving Language Plasticity via Pretraining with Active Forgetting

Yihong Chen · Kelly Marchisio · Roberta Raileanu · David Adelani · Pontus Lars Erik Saito Stenetorp · Sebastian Riedel · Mikel Artetxe

Pengi: An Audio Language Model for Audio Tasks

Soham Deshmukh · Benjamin Elizalde · Rita Singh · Huaming Wang

Continual Learning for Instruction Following from Realtime Feedback

Alane Suhr · Yoav Artzi

Extensible Prompts for Language Models on Zero-shot Language Style Customization

Tao Ge · Hu Jing · Li Dong · Shaoguang Mao · Yan Xia · Xun Wang · Si-Qing Chen · Furu Wei

EvoPrompting: Language Models for Code-Level Neural Architecture Search

Angelica Chen · David Dohan · David Dohan · David So

AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web

Michael Schlichtkrull · Zhijiang Guo · Andreas Vlachos

SPRING: Studying Papers and Reasoning to play Games

Yue Wu · So Yeon Min · Shrimai Prabhumoye · Yonatan Bisk · Russ Salakhutdinov · Amos Azaria · Tom Mitchell · Yuanzhi Li

Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision

Zhiqing Sun · Yikang Shen · Qinhong Zhou · Hongxin Zhang · Zhenfang Chen · David Cox · Yiming Yang · Chuang Gan

Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting

Hejie Cui · Xinyu Fang · Zihan Zhang · Ran Xu · Xuan Kan · Xin Liu · Yue Yu · Manling Li · Yangqiu Song · Carl Yang

Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale

Matthew Le · Apoorv Vyas · Bowen Shi · Brian Karrer · Leda Sari · Rashel Moritz · Mary Williamson · Vimal Manohar · Yossi Adi · Jay Mahadeokar · Wei-Ning Hsu

Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline

Zangwei Zheng · Zangwei Zheng · Xiaozhe Ren · Fuzhao Xue · Yang Luo · Xin Jiang · Yang You

Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer

Jianwei Zhang · Suren Jayasuriya · Visar Berisha

InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding

Junda Wu · Junda Wu · Tong Yu · Rui Wang · Rui Wang · Zhao Song · Ruiyi Zhang · Handong Zhao · Chaochao Lu · Shuai Li · Ricardo Henao

StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models

Yinghao Aaron Li · Cong Han · Vinay Raghavan · Gavin Mischler · Nima Mesgarani

The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications

Mirac Suzgun · Luke Melas-Kyriazi · Suproteem Sarkar · Scott D Kominers · Stuart Shieber

Learning and processing the ordinal information of temporal sequences in recurrent neural circuits

xiaolong zou · Zhikun Chu · Qinghai Guo · Jie Cheng · Bo Ho · Si Wu · Yuanyuan Mi

Towards robust and generalizable representations of extracellular data using contrastive learning

Ankit Vishnubhotla · Charlotte Loh · Akash Srivastava · Liam Paninski · Cole Hurwitz

Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies

Wei Fang · Zhaofei Yu · Zhaokun Zhou · Ding Chen · Yanqi Chen · Zhengyu Ma · Timothée Masquelier · Yonghong Tian

A polar prediction model for learning to represent visual transformations

Pierre-Étienne Fiquet · Eero Simoncelli

Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels

Vijay Veerabadran · Srinivas Ravishankar · Yuan Tang · Ritik Raina · Virginia de Sa

Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability

David Liu · Mate Lengyel

Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors

Paul Scotti · Atmadeep Banerjee · Jimmie Goode · Stepan Shabalin · Alex Nguyen · ethan cohen · Aidan Dempster · Nathalie Verlinde · Elad Yundler · David Weisberg · Kenneth Norman · Tanishq Abraham

Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes

Aran Nayebi · Rishi Rajalingham · Mehrdad Jazayeri · Guangyu Robert Yang

Brain Dissection: fMRI-trained Networks Reveal Spatial Selectivity in the Processing of Natural Images

Gabriel Sarch · Michael Tarr · Katerina Fragkiadaki · Leila Wehbe

Alleviating the Semantic Gap for Generalized fMRI-to-Image Reconstruction

Tao Fang · Qian Zheng · Gang Pan

Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations

Thomas Yerxa · Yilun Kuang · Eero Simoncelli · SueYeon Chung

An information-theoretic quantification of the content of communication between brain regions

Marco Celotto · Jan Bím · Alejandro Tlaie · Vito De Feo · Alessandro Toso · Stefan Lemke · Daniel Chicharro · Hamed Nili · Malte Bieler · Ileana Hanganu-Opatz · Tobias Donner · Andrea Brovelli · Stefano Panzeri

Formalizing locality for normative synaptic plasticity models

Colin Bredenberg · Ezekiel Williams · Cristina Savin · Blake Richards · Guillaume Lajoie

D-CIPHER: Discovery of Closed-form Partial Differential Equations

Krzysztof Kacprzyk · Zhaozhi Qian · Mihaela van der Schaar

Swarm Reinforcement Learning for Adaptive Mesh Refinement

Niklas Freymuth · Philipp Dahlinger · Tobias Würth · Simon Reisch · Luise Kärger · Gerhard Neumann

Versatile Energy-Based Probabilistic Models for High Energy Physics

Taoli Cheng · Aaron Courville

CARE: Modeling Interacting Dynamics Under Temporal Environmental Variation

Xiao Luo · Haixin Wang · Zijie Huang · Huiyu Jiang · Abhijeet Gangan · Song Jiang · Yizhou Sun

Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation

Kirill Neklyudov · Jannes Nys · Luca Thiede · Juan Carrasquilla · Qiang Liu · Max Welling · Alireza Makhzani

NVFi: Neural Velocity Fields for 3D Physics Learning from Dynamic Videos

Jinxi Li · Ziyang Song · Bo Yang

DiffVL: Scaling Up Soft Body Manipulation using Vision-Language Driven Differentiable Physics

Zhiao Huang · Feng Chen · Yewen Pu · Chunru Lin · Hao Su · Chuang Gan

Neural Lighting Simulation for Urban Scenes

Ava Pun · Gary Sun · Jingkang Wang · Yun Chen · Ze Yang · Sivabalan Manivasagam · Wei-Chiu Ma · Raquel Urtasun

Frequency-Enhanced Data Augmentation for Vision-and-Language Navigation

Keji He · Chenyang Si · Zhihe Lu · Yan Huang · Liang Wang · Xinchao Wang

What Planning Problems Can A Relational Neural Network Solve?

Jiayuan Mao · Tomás Lozano-Pérez · Josh Tenenbaum · Leslie Kaelbling

Enhancing Robot Program Synthesis Through Environmental Context

Tianyi Chen · Qidi Wang · Zhen Dong · Liwei Shen · Xin Peng

Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies

Hanna Ziesche · Leonel Rozo

Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought

Yuki Wang · Gonzalo Gonzalez-Pumariega · Yash Sharma · Sanjiban Choudhury

Switching Autoregressive Low-rank Tensor Models

Hyun Dong Lee · Andrew Warrington · Joshua Glaser · Scott Linderman

DataComp: In search of the next generation of multimodal datasets

Geometry-Aware Adaptation for Pretrained Models

Nicholas Roberts · Xintong Li · Dyah Adila · Sonia Cromp · Tzu-Heng Huang · Jitian Zhao · Frederic Sala

Adversarial Learning for Feature Shift Detection and Correction

Míriam Barrabés · Daniel Mas Montserrat · Margarita Geleta · Xavier Giró-i-Nieto · Alexander Ioannidis

Learning Dictionary for Visual Attention

Yingjie Liu · Xuan Liu · Hui Yu · XUAN TANG · Xian Wei

Modality-Independent Teachers Meet Weakly-Supervised Audio-Visual Event Parser

Yung-Hsuan Lai · Yen-Chun Chen · Frank Wang

Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data

Jang-Hyun Kim · Sangdoo Yun · Hyun Oh Song

Permutation Equivariant Neural Functionals

Allan Zhou · Kaien Yang · Kaylee Burns · Adriano Cardace · Yiding Jiang · Samuel Sokota · J. Zico Kolter · Chelsea Finn

Explore In-Context Learning for 3D Point Cloud Understanding

Zhongbin Fang · Xiangtai Li · Xia Li · Xia Li · Joachim M Buhmann · Chen Change Loy · Mengyuan Liu

Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design

Ibrahim Alabdulmohsin · Xiaohua Zhai · Alexander Kolesnikov · Lucas Beyer

Universality and Limitations of Prompt Tuning

Yihan Wang · Jatin Chauhan · Wei Wang · Cho-Jui Hsieh

MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates

Mohammad Mozaffari · Sikan Li · Zhao Zhang · Maryam Mehri Dehnavi

Knowledge Distillation for High Dimensional Search Index

Zepu Lu · Jin Chen · Defu Lian · ZAIXI ZHANG · Yong Ge · Enhong Chen

Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models

Leonardo Galli · Holger Rauhut · Mark Schmidt

Fine-Grained Visual Prompting

Lingfeng Yang · Yueze Wang · Yueze Wang · Xiang Li · Xinlong Wang · Jian Yang

MIMONets: Multiple-Input-Multiple-Output Neural Networks Exploiting Computation in Superposition

Nicolas Menet · Michael Hersche · Geethan Karunaratne · Luca Benini · Abu Sebastian · Abbas Rahimi

ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer

Haoran You · Huihong Shi · Yipin Guo · Yingyan Lin

CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence

Bong Gyun Kang · HyunGi Kim · Dahuin Jung · Sungroh Yoon

Softmax Output Approximation for Activation Memory-Efficient Training of Attention-based Networks

Changhyeon Lee · Seulki Lee

PDP: Parameter-free Differentiable Pruning is All You Need

Minsik Cho · Saurabh Adya · Devang Naik

Normalization Layers Are All That Sharpness-Aware Minimization Needs

Maximilian Mueller · Tiffany Vlaar · David Rolnick · Matthias Hein

Principled Weight Initialisation for Input-Convex Neural Networks

Pieter-Jan Hoedt · Günter Klambauer

Direct Training of SNN using Local Zeroth Order Method

Bhaskar Mukhoty · Velibor Bojkovic · William de Vazelhes · Xiaohan Zhao · Giulia De Masi · Huan Xiong · Bin Gu

A fast heuristic to optimize time-space tradeoff for large models

Akifumi Imanishi · Zijian Xu · Masayuki Takagi · Sixue Wang · Emilio Castillo

Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training

Yefan Zhou · TIANYU PANG · Keqin Liu · charles martin · Michael Mahoney · Yaoqing Yang

Memory Efficient Optimizers with 4-bit States

Bingrui Li · Jianfei Chen · Jun Zhu

Multi-modal Queried Object Detection in the Wild

Yifan Xu · Mengdan Zhang · Chaoyou Fu · Peixian Chen · Xiaoshan Yang · Ke Li · Changsheng Xu

Unlimiformer: Long-Range Transformers with Unlimited Length Input

Amanda Bertsch · Uri Alon · Graham Neubig · Matthew Gormley

Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion

Kunxun Qi · Jianfeng Du · Hai Wan

Coop: Memory is not a Commodity

Jianhao Zhang · Shihan Ma · Peihong Liu · Jinhui Yuan

Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement

Hui Yuan · Kaixuan Huang · Chengzhuo Ni · Minshuo Chen · Mengdi Wang

TabMT: Generating tabular data with masked transformers

Manbir Gulati · Paul Roysdon

Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context

Lakshya A Agrawal · Aditya Kanade · Navin Goyal · Shuvendu Lahiri · Sriram Rajamani

DreamHuman: Animatable 3D Avatars from Text

Nikos Kolotouros · Thiemo Alldieck · Andrei Zanfir · Eduard Bazavan · Mihai Fieraru · Cristian Sminchisescu

Generating Behaviorally Diverse Policies with Latent Diffusion Models

Shashank Hegde · Sumeet Batra · K.R. Zentner · Gaurav Sukhatme

GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks

Zhonghang Li · Lianghao Xia · Yong Xu · Chao Huang

Spontaneous symmetry breaking in generative diffusion models

Gabriel Raya · Luca Ambrogioni

Metropolis Sampling for Constrained Diffusion Models

Nic Fishman · Leo Klarner · Emile Mathieu · Michael Hutchinson · Valentin De Bortoli

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models

Zhendong Wang · Yifan Jiang · Huangjie Zheng · Peihao Wang · Pengcheng He · Zhangyang "Atlas" Wang · Weizhu Chen · Mingyuan Zhou

PCF-GAN: generating sequential data via the characteristic function of measures on the path space

Hang Lou · Siran Li · Hao Ni

InsActor: Instruction-driven Physics-based Characters

Jiawei Ren · Mingyuan Zhang · Cunjun Yu · Xiao Ma · Liang Pan · Ziwei Liu

Parts of Speech–Grounded Subspaces in Vision-Language Models

James Oldfield · Christos Tzelepis · Yannis Panagakis · Mihalis Nicolaou · Ioannis Patras

Object-Centric Slot Diffusion

Jindong Jiang · Fei Deng · Gautam Singh · Sungjin Ahn

AdaVAE: Bayesian Structural Adaptation for Variational Autoencoders

Paribesh Regmi · Rui Li

Are Diffusion Models Vision-And-Language Reasoners?

Benno Krojer · Elinor Poole-Dayan · Vikram Voleti · Chris Pal · Siva Reddy

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models

Shuchen Xue · Mingyang Yi · Weijian Luo · Shifeng Zhang · Jiacheng Sun · Zhenguo Li · Zhi-Ming Ma

Learning Energy-Based Prior Model with Diffusion-Amortized MCMC

Peiyu Yu · Yaxuan Zhu · Sirui Xie · Xiaojian (Shawn) Ma · Ruiqi Gao · Song-Chun Zhu · Ying Nian Wu

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences

Minsu Kim · Federico Berto · Sungsoo Ahn · Jinkyoo Park

Domain Re-Modulation for Few-Shot Generative Domain Adaptation

Yi Wu · Ziqiang Li · Chaoyue Wang · Heliang Zheng · Shanshan Zhao · Bin Li · Dacheng Tao

Non-adversarial training of Neural SDEs with signature kernel scores

Zacharia Issa · Blanka Horvath · Maud Lemercier · Cristopher Salvi

Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples

Marco Jiralerspong · Joey Bose · Ian Gemp · Chongli Qin · Yoram Bachrach · Gauthier Gidel

Simple and Controllable Music Generation

Jade Copet · Felix Kreuk · Itai Gat · Tal Remez · David Kant · Gabriel Synnaeve · Yossi Adi · Alexandre Defossez

Diffusion Self-Guidance for Controllable Image Generation

Dave Epstein · Allan Jabri · Ben Poole · Alexei Efros · Aleksander Holynski

Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion

Shengqiong Wu · Hao Fei · Hanwang Zhang · Tat-Seng Chua

Norm-guided latent space exploration for text-to-image generation

Dvir Samuel · Rami Ben-Ari · Nir Darshan · Haggai Maron · Gal Chechik

Statistical Knowledge Assessment for Large Language Models

Qingxiu Dong · Jingjing Xu · Lingpeng Kong · Zhifang Sui · Lei Li

Free-Bloom: Zero-Shot Text-to-Video Generator with LLM Director and LDM Animator

Hanzhuo Huang · Yufan Feng · Cheng Shi · Lan Xu · Jingyi Yu · Sibei Yang

Generator Born from Classifier

Runpeng Yu · Xinchao Wang

Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting

Marcel Kollovieh · Abdul Fatir Ansari · Michael Bohlke-Schneider · Jasper Zschiegner · Hao Wang · Yuyang (Bernie) Wang

On the choice of Perception Loss Function for Learned Video Compression

Sadaf Salehkalaibar · Truong Buu Phan · Jun Chen · Wei Yu · Ashish Khisti

DiffComplete: Diffusion-based Generative 3D Shape Completion

Ruihang Chu · Enze Xie · Shentong Mo · Shentong Mo · Zhenguo Li · Matthias Niessner · Chi-Wing Fu · Jiaya Jia

The CLIP Model is Secretly an Image-to-Prompt Converter

Yuxuan Ding · Chunna Tian · Haoxuan Ding · Lingqiao Liu

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation

Zhengyi Wang · Cheng Lu · Yikai Wang · Fan Bao · Chongxuan LI · Hang Su · Jun Zhu

Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation

Susung Hong · Donghoon Ahn · Seungryong Kim

Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion

Hyuna Cho · Minjae Jeong · Sooyeon Jeon · Sungsoo Ahn · Won Hwa Kim

Diffusion Schrödinger Bridge Matching

Yuyang Shi · Valentin De Bortoli · Andrew Campbell · Arnaud Doucet

Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models

Geon Yeong Park · Jeongsol Kim · Beomsu Kim · Sang Wan Lee · Jong Chul Ye

Parsel🐍: Algorithmic Reasoning with Language Models by Composing Decompositions

Eric Zelikman · Qian Huang · Gabriel Poesia · Noah Goodman · Nick Haber

Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models

Alvin Heng · Harold Soh

Adapting Neural Link Predictors for Data-Efficient Complex Query Answering

Erik Arakelyan · Pasquale Minervini · Daniel Daza · Michael Cochez · Isabelle Augenstein

GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation

Mingxuan Ju · Tong Zhao · Wenhao Yu · Neil Shah · Yanfang Ye

Transformers over Directed Acyclic Graphs

Yuankai Luo · Veronika Thost · Lei Shi

A new perspective on building efficient and expressive 3D equivariant graph neural networks

weitao Du · Yuanqi Du · Limei Wang · Dieqiao Feng · Guifeng Wang · Shuiwang Ji · Carla Gomes · Zhi-Ming Ma

Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization

Haonan Yuan · Qingyun Sun · Xingcheng Fu · Ziwei Zhang · Cheng Ji · Hao Peng · Jianxin Li

Train Once and Explain Everywhere: Pre-training Interpretable Graph Neural Networks

Jun Yin · Chaozhuo Li · Hao Yan · Jianxun Lian · Senzhang Wang

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

Haitao Mao · Zhikai Chen · Wei Jin · Haoyu Han · Yao Ma · Tong Zhao · Neil Shah · Jiliang Tang

From Trainable Negative Depth to Edge Heterophily in Graphs

Yuchen Yan · Yuzhong Chen · Huiyuan Chen · Minghua Xu · Mahashweta Das · Hao Yang · Hanghang Tong

Going beyond persistent homology using persistent homology

Johanna Immonen · Amauri Souza · Vikas Garg

Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis

Junfeng Fang · Wei Liu · Yuan Gao · Zemin Liu · An Zhang · Xiang Wang · Xiangnan He

Limits, approximation and size transferability for GNNs on sparse graphs via graphops

Thien Le · Stefanie Jegelka

Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift

Yongduo Sui · Qitian Wu · Jiancan Wu · Qing Cui · Longfei Li · Jun Zhou · Xiang Wang · Xiangnan He

Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts

Gleb Bazhenov · Denis Kuznedelev · Andrey Malinin · Artem Babenko · Liudmila Prokhorenkova

Maximum Independent Set: Self-Training through Dynamic Programming

Lorenzo Brusca · Lars C.P.M. Quaedvlieg · Stratis Skoulakis · Grigorios Chrysos · Volkan Cevher

ESSEN: Improving Evolution State Estimation for Temporal Networks using Von Neumann Entropy

Qiyao Huang · Yingyue Zhang · Zhihong Zhang · Edwin Hancock

When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability

Sitao Luan · Chenqing Hua · Minkai Xu · Qincheng Lu · Jiaqi Zhu · Xiao-Wen Chang · Jie Fu · Jure Leskovec · Doina Precup

GALOPA: Graph Transport Learning with Optimal Plan Alignment

Yejiang Wang · Yuhai Zhao · Daniel Zhengkui Wang · Ling Li

Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First

Zheng Zhang · Junxiang Wang · Liang Zhao

GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels

Xin Zheng · Miao Zhang · Chunyang Chen · Soheila Molaei · Chuan Zhou · Shirui Pan

Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints

Jiaxin Bai · Xin Liu · Weiqi Wang · Chen Luo · Yangqiu Song

FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks

Yuhang Yao · Weizhao Jin · Srivatsan Ravi · Carlee Joe-Wong

Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection

Hezhe Qiao · Guansong Pang

Interpretable Prototype-based Graph Information Bottleneck

Sangwoo Seo · Sungwon Kim · Chanyoung Park

Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance

Jinwoo Kim · Dat Nguyen · Ayhan Suleymanzade · Hyeokjun An · Seunghoon Hong

Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily

Langzhang Liang · Xiangjing Hu · Zenglin Xu · Zixing Song · Irwin King

Clifford Group Equivariant Neural Networks

David Ruhe · Johannes Brandstetter · Patrick Forré

Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective

Zihan Luo · Hong Huang · Jianxun Lian · Xiran Song · Xing Xie · Hai Jin

TriRE: A Multi-Mechanism Learning Paradigm for Continual Knowledge Retention and Promotion

Preetha Vijayan · Prashant Bhat · Bahram Zonooz · Elahe Arani

Latent Space Translation via Semantic Alignment

Valentino Maiorca · Luca Moschella · Antonio Norelli · Marco Fumero · Francesco Locatello · Emanuele Rodolà

Understanding and Improving Feature Learning for Out-of-Distribution Generalization

Yongqiang Chen · Wei Huang · Kaiwen Zhou · Yatao Bian · Bo Han · James Cheng

Geodesic Multi-Modal Mixup for Robust Fine-Tuning

Changdae Oh · Junhyuk So · Hoyoon Byun · YongTaek Lim · Minchul Shin · Jong-June Jeon · Kyungwoo Song

RGMIL: Guide Your Multiple-Instance Learning Model with Regressor

Zhaolong Du · Shasha Mao · Yimeng Zhang · Shuiping Gou · Licheng Jiao · Lin Xiong

PDF: Point Diffusion Implicit Function for Large-scale Scene Neural Representation

Yuhan Ding · Fukun Yin · Jiayuan Fan · Hui Li · Xin Chen · Wen Liu · Chongshan Lu · Gang Yu · Tao Chen

A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints

Kareem Ahmed · Kai-Wei Chang · Guy Van den Broeck

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems

Benjamin Coleman · Wang-Cheng Kang · Matthew Fahrbach · Ruoxi Wang · Lichan Hong · Ed Chi · Derek Cheng

Gradient Flossing: Improving Gradient Descent through Dynamic Control of Jacobians

Rainer Engelken

Simultaneous embedding of multiple attractor manifolds in a recurrent neural network using constrained gradient optimization

Haggai Agmon · Yoram Burak

Recursion in Recursion: Two-Level Nested Recursion for Length Generalization with Scalability

Jishnu Ray Chowdhury · Cornelia Caragea

Adversarial Training from Mean Field Perspective

Soichiro Kumano · Hiroshi Kera · Toshihiko Yamasaki

Convolutional Visual Prompt for Robust Visual Perception

Yun-Yun Tsai · Chengzhi Mao · Junfeng Yang

Learning Provably Robust Estimators for Inverse Problems via Jittering

Anselm Krainovic · Mahdi Soltanolkotabi · Reinhard Heckel

SOL: Sampling-based Optimal Linear bounding of arbitrary scalar functions

Yuriy Biktairov · Jyotirmoy Deshmukh

Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More

Jan Schuchardt · Yan Scholten · Stephan Günnemann

RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion

Zhuoqun Huang · Neil G Marchant · Keane Lucas · Lujo Bauer · Olga Ohrimenko · Benjamin Rubinstein

Revisiting Visual Model Robustness: A Frequency Long-Tailed Distribution View

Zhiyu Lin · Yifei Gao · Yunfan Yang · Jitao Sang

Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks

Andong Wang · Chao Li · Mingyuan Bai · Zhong Jin · Guoxu Zhou · Qibin Zhao

DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework

Siran Dai · Qianqian Xu · Zhiyong Yang · Xiaochun Cao · Qingming Huang

FedGame: A Game-Theoretic Defense against Backdoor Attacks in Federated Learning

Jinyuan Jia · Zhuowen Yuan · Dinuka Sahabandu · Luyao Niu · Arezoo Rajabi · Bhaskar Ramasubramanian · Bo Li · Radha Poovendran

Label Poisoning is All You Need

Rishi Jha · Jonathan Hayase · Sewoong Oh

Adversarial Examples Are Not Real Features

Ang Li · Yifei Wang · Yiwen Guo · Yisen Wang

Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification

Kanishk Jain · Kanishk Jain · Shyamgopal Karthik · Vineet Gandhi

Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models

Andy Zhou · Jindong Wang · Yu-Xiong Wang · Haohan Wang

Theoretically Guaranteed Bidirectional Data Rectification for Robust Sequential Recommendation

Yatong Sun · Bin Wang · Zhu Sun · Xiaochun Yang · Yan Wang

Certifiably Robust Graph Contrastive Learning

Minhua Lin · Teng Xiao · Enyan Dai · Xiang Zhang · Suhang Wang

Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning

Marina Munkhoeva · Ivan Oseledets

FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space

Shengzhong Liu · Tomoyoshi Kimura · Dongxin Liu · Ruijie Wang · Jinyang Li · Suhas Diggavi · Mani Srivastava · Tarek Abdelzaher

Segment Any Point Cloud Sequences by Distilling Vision Foundation Models

Youquan Liu · Lingdong Kong · Jun CEN · Runnan Chen · Wenwei Zhang · Liang Pan · Kai Chen · Ziwei Liu

Training Transitive and Commutative Multimodal Transformers with LoReTTa

Manuel Tran · Yashin Dicente Cid · Amal Lahiani · Fabian Theis · Tingying Peng · Eldad Klaiman

Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series

Yihe Wang · Yu Han · Haishuai Wang · Xiang Zhang

Representation Learning via Consistent Assignment of Views over Random Partitions

Thalles Santos Silva · Adín Ramírez Rivera

Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods

Tobit Klug · Dogukan Atik · Reinhard Heckel

Combating Representation Learning Disparity with Geometric Harmonization

Zhihan Zhou · Jiangchao Yao · Feng Hong · Ya Zhang · Bo Han · Yanfeng Wang

Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense

Zunzhi You · Daochang Liu · Bohyung Han · Chang Xu

Language-based Action Concept Spaces Improve Video Self-Supervised Learning

Kanchana Ranasinghe · Michael S Ryoo

PointGPT: Auto-regressively Generative Pre-training from Point Clouds

Guangyan Chen · Meiling Wang · Yi Yang · Kai Yu · Li Yuan · Yufeng Yue

CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss

Rakshith Sharma Srinivasa · Jaejin Cho · Chouchang Yang · Yashas Malur Saidutta · Ching-Hua Lee · Yilin Shen · Hongxia Jin

ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling

Yuqi Chen · Kan Ren · Yansen Wang · Yuchen Fang · Weiwei Sun · Dongsheng Li

SutraNets: Sub-series Autoregressive Networks for Long-Sequence, Probabilistic Forecasting

Shane Bergsma · Tim Zeyl · Lei Guo

State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory

Shida Wang · Beichen Xue

Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

Kun Yi · Qi Zhang · Wei Fan · Shoujin Wang · Pengyang Wang · Hui He · Ning An · Defu Lian · Longbing Cao · Zhendong Niu

MultiMoDN—Multimodal, Multi-Task, Interpretable Modular Networks

Vinitra Swamy · Malika Satayeva · Jibril Frej · Thierry Bossy · Thijs Vogels · Martin Jaggi · Tanja Käser · Mary-Anne Hartley

Homotopy-based training of NeuralODEs for accurate dynamics discovery

Joon-Hyuk Ko · Hankyul Koh · Nojun Park · Wonho Jhe

SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling

Jiaxiang Dong · Jiaxiang Dong · Haixu Wu · Haoran Zhang · Li Zhang · Jianmin Wang · Mingsheng Long

Multi Time Scale World Models

Vaisakh Shaj Kumar · SALEH GHOLAM ZADEH · Ozan Demir · Luiz Douat · Gerhard Neumann

Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction

Chih-Yu (Andrew) Lai · Fan-Keng Sun · Zhengqi Gao · Jeffrey H Lang · Duane Boning

Generalization bounds for neural ordinary differential equations and deep residual networks

Pierre Marion · Pierre Marion

Leveraging the two-timescale regime to demonstrate convergence of neural networks

Pierre Marion · Pierre Marion · Raphaël Berthier

The Learnability of In-Context Learning

Noam Wies · Yoav Levine · Amnon Shashua

How do Minimum-Norm Shallow Denoisers Look in Function Space?

Chen Zeno · Greg Ongie · Yaniv Blumenfeld · Nir Weinberger · Daniel Soudry

Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent

Jin-Hui Wu · Shao-Qun Zhang · Yuan Jiang · Zhi-Hua Zhou

Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization

Yajie Bao · Amarda Shehu · Mingrui Liu

Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks

Feng Chen · Daniel Kunin · Atsushi Yamamura · Surya Ganguli

Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks

Blake Bordelon · Cengiz Pehlevan

On the impact of activation and normalization in obtaining isometric embeddings at initialization

Amir Joudaki · Hadi Daneshmand · Francis Bach

Spectral Evolution and Invariance in Linear-width Neural Networks

Zhichao Wang · Andrew Engel · Anand D Sarwate · Ioana Dumitriu · Tony Chiang

Theoretical and Practical Perspectives on what Influence Functions Do

Andrea Schioppa · Katja Filippova · Ivan Titov · Polina Zablotskaia

Neural (Tangent Kernel) Collapse

Mariia Seleznova · Dana Weitzner · Raja Giryes · Gitta Kutyniok · Hung-Hsu Chou

Relative Entropic Optimal Transport: a (Prior-aware) Matching Perspective to (Unbalanced) Classification

Liangliang Shi · Haoyu Zhen · Gu Zhang · Junchi Yan

Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective

Zeyu Zhang · Yi Su · Hui Yuan · Yiran Wu · Rishab Balasubramanian · Qingyun Wu · Huazheng Wang · Mengdi Wang

Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search

Indradyumna Roy · Rishi Agarwal · Soumen Chakrabarti · Anirban Dasgupta · Abir De

Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models

Naoki Egami · Musashi Hinck · Brandon Stewart · Hanying Wei

AMDP: An Adaptive Detection Procedure for False Discovery Rate Control in High-Dimensional Mediation Analysis

Jiarong Ding · Xuehu ZHU

Identifiability Guarantees for Causal Disentanglement from Soft Interventions

Jiaqi Zhang · Kristjan Greenewald · Chandler Squires · Akash Srivastava · Karthikeyan Shanmugam · Caroline Uhler

K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing

Shuai Li · Yingjie Zhang · Hongtu Zhu · Christina Wang · Hai Shu · Ziqi Chen · Zhuoran Sun · Yanfeng Yang

Bayesian Active Causal Discovery with Multi-Fidelity Experiments

Zeyu Zhang · Chaozhuo Li · Xu Chen · Xing Xie

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data

Siyuan Guo · Viktor Toth · Bernhard Schölkopf · Ferenc Huszar

Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge

Abhin Shah · Karthikeyan Shanmugam · Murat Kocaoglu

Sharp Bounds for Generalized Causal Sensitivity Analysis

Dennis Frauen · Valentyn Melnychuk · Stefan Feuerriegel

Meek Separators and Their Applications in Targeted Causal Discovery

Kirankumar Shiragur · Jiaqi Zhang · Caroline Uhler

Causal Effect Identification in Uncertain Causal Networks

Sina Akbari · Fateme Jamshidi · Ehsan Mokhtarian · Matthew Vowels · Jalal Etesami · Negar Kiyavash

Counterfactual Evaluation of Peer-Review Assignment Policies

Martin Saveski · Steven Jecmen · Nihar Shah · Johan Ugander

A Causal Framework for Decomposing Spurious Variations

Drago Plecko · Elias Bareinboim

On Learning Necessary and Sufficient Causal Graphs

Hengrui Cai · Yixin Wang · Michael Jordan · Rui Song

$p$-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison

Kai Klede · Thomas Altstidl · Dario Zanca · Bjoern Eskofier

Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources

Feiyang Kang · Hoang Anh Just · Anit Kumar Sahu · Ruoxi Jia

Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy

Lei Xu · Lei Chen · Rong Wang · Feiping Nie · Xuelong Li

False Discovery Proportion control for aggregated Knockoffs

Alexandre Blain · Bertrand Thirion · Olivier Grisel · Pierre Neuvial

Statistical Insights into HSIC in High Dimensions

Tao Zhang · Yaowu Zhang · Tingyou Zhou

Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models

Anant Raj · Umut Simsekli · Alessandro Rudi

Kernel-Based Tests for Likelihood-Free Hypothesis Testing

Patrik Robert Gerber · Tianze Jiang · Yury Polyanskiy · Rui Sun

Contextual Gaussian Process Bandits with Neural Networks

Haoting Zhang · Jinghai He · Rhonda Righter · Zuo-Jun Shen · Zeyu Zheng

Towards Optimal Caching and Model Selection for Large Model Inference

Banghua Zhu · Ying Sheng · Lianmin Zheng · Clark Barrett · Michael Jordan · Jiantao Jiao

On Private and Robust Bandits

Yulian Wu · Xingyu Zhou · Youming Tao · Di Wang

How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget

Guy Hacohen · Daphna Weinshall

Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits

Muhammad Faaiz Taufiq · Arnaud Doucet · Rob Cornish · Jean-Francois Ton

Multi-Fidelity Multi-Armed Bandits Revisited

Xuchuang Wang · Qingyun Wu · Wei Chen · John C.S. Lui

Meta-Learning Adversarial Bandit Algorithms

Misha Khodak · Ilya Osadchiy · Keegan Harris · Maria-Florina Balcan · Kfir Y. Levy · Ron Meir · Steven Wu

A General Framework for Robust G-Invariance in G-Equivariant Networks

Sophia Sanborn · Sophia Sanborn · Nina Miolane

A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions

David Loiseaux · Mathieu Carrière · Andrew Blumberg

Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings

Yi Ren · Samuel Lavoie · Michael Galkin · Danica J. Sutherland · Aaron Courville

On the Identifiability of Sparse ICA without Assuming Non-Gaussianity

Ignavier Ng · Yujia Zheng · Xinshuai Dong · Kun Zhang

Contrastive Training of Complex-Valued Autoencoders for Object Discovery

Aleksandar Stanić · Anand Gopalakrishnan · Kazuki Irie · Jürgen Schmidhuber

Learning Linear Causal Representations from Interventions under General Nonlinear Mixing

Simon Buchholz · Goutham Rajendran · Elan Rosenfeld · Bryon Aragam · Bernhard Schölkopf · Pradeep Ravikumar

DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries

Joshua Engels · Benjamin Coleman · Vihan Lakshman · Anshumali Shrivastava

A Unified Fast Gradient Clipping Framework for DP-SGD

Weiwei Kong · Andres Munoz Medina

Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics

Guillaume Mahey · Laetitia Chapel · Gilles Gasso · Clément Bonet · Nicolas Courty

One Fits All: Power General Time Series Analysis by Pretrained LM

Tian Zhou · Peisong Niu · xue wang · Liang Sun · Rong Jin

Generalized test utilities for long-tail performance in extreme multi-label classification

Erik Schultheis · Marek Wydmuch · Wojciech Kotlowski · Rohit Babbar · Krzysztof Dembczynski

Multi-task learning with summary statistics

Parker Knight · Rui Duan

ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion

Yingjun Du · Zehao Xiao · Shengcai Liao · Cees Snoek

Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning

Yizhou Zhang · Jingchao Ni · Wei Cheng · Zhengzhang Chen · Liang Tong · Haifeng Chen · Yan Liu

Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks

Jiarong Xu · Renhong Huang · XIN JIANG · Yuxuan Cao · Carl Yang · Chunping Wang · YANG YANG

Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation

David Brandfonbrener · David Brandfonbrener · Ofir Nachum · Joan Bruna

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining

Sang Michael Xie · Hieu Pham · Xuanyi Dong · Nan Du · Hanxiao Liu · Yifeng Lu · Percy Liang · Quoc V Le · Tengyu Ma · Adams Wei Yu

Differentiable Clustering with Perturbed Spanning Forests

Lawrence Stewart · Francis Bach · Felipe Llinares-Lopez · Quentin Berthet

Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery

Katie Luo · Zhenzhen Liu · Xiangyu Chen · Yurong You · Sagie Benaim · Cheng Perng Phoo · Mark Campbell · Wen Sun · Bharath Hariharan · Kilian Weinberger

RETVec: Resilient and Efficient Text Vectorizer

Elie Bursztein · Marina Zhang · Owen Vallis · XINYU JIA · Alexey Kurakin

Semi-Supervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation

Weihang Dai · Yao DU · Hanru Bai · Kwang-Ting Cheng · Xiaomeng Li

Doubly-Robust Self-Training

Banghua Zhu · Mingyu Ding · Philip Jacobson · Ming Wu · Wei Zhan · Michael Jordan · Jiantao Jiao

Unsupervised Anomaly Detection with Rejection

Lorenzo Perini · Jesse Davis

Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information

Arman Zharmagambetov · Brandon Amos · Aaron Ferber · Aaron Ferber · Taoan Huang · Bistra Dilkina · Yuandong Tian

How Does Adaptive Optimization Impact Local Neural Network Geometry?

Kaiqi Jiang · Dhruv Malik · Yuanzhi Li

Efficient Hyper-parameter Optimization with Cubic Regularization

Zhenqian Shen · Hansi Yang · Yong Li · James Kwok · Quanming Yao

Energy-based learning algorithms for analog computing: a comparative study

Benjamin Scellier · Maxence Ernoult · Jack Kendall · Suhas Kumar

BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization

Chen Fan · Gaspard Choné-Ducasse · Mark Schmidt · Christos Thrampoulidis

Online Adaptive Policy Selection in Time-Varying Systems: No-Regret via Contractive Perturbations

Yiheng Lin · James A. Preiss · Emile Anand · Yingying Li · Yingying Li · Yisong Yue · Adam Wierman

Continuous-time Analysis of Anchor Acceleration

Jaewook Suh · Jisun Park · Ernest Ryu

Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization

Liang Zhang · Junchi YANG · Amin Karbasi · Niao He

Unsupervised Learning for Solving the Travelling Salesman Problem

Yimeng Min · Yiwei Bai · Carla Gomes

Bicriteria Approximation Algorithms for the Submodular Cover Problem

Wenjing Chen · Victoria Crawford

Online Ad Allocation with Predictions

Fabian Spaeh · Alina Ene

Block Broyden's Methods for Solving Nonlinear Equations

Chengchang Liu · Cheng Chen · Luo Luo · John C.S. Lui

FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout

Irene Wang · Prashant Nair · Divya Mahajan

Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning

Junyi Li · Heng Huang

2Direction: Theoretically Faster Distributed Training with Bidirectional Communication Compression

Alexander Tyurin · Peter Richtarik

Private Federated Frequency Estimation: Adapting to the Hardness of the Instance

Jingfeng Wu · Wennan Zhu · Peter Kairouz · Vladimir Braverman

A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting

Alexander Tyurin · Peter Richtarik

Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices

Kilian Pfeiffer · Ramin Khalili · Joerg Henkel

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning

Yue Tan · Chen Chen · Weiming Zhuang · Xin Dong · Lingjuan Lyu · Guodong Long

Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data

Sai Aparna Aketi · Abolfazl Hashemi · Kaushik Roy

L2T-DLN: Learning to Teach with Dynamic Loss Network

Zhaoyang Hai · Liyuan Pan · Xiabi Liu · Zhengzheng Liu · Mirna Yunita

Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks

Eeshaan Jain · Tushar Nandy · Gaurav Aggarwal · Ashish Tendulkar · Rishabh Iyer · Abir De

Learning to Configure Separators in Branch-and-Cut

Sirui Li · Wenbin Ouyang · Max Paulus · Cathy Wu

Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing

Ziye Ma · Javad Lavaei · Somayeh Sojoudi

Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization

Quanqi Hu · Dixian Zhu · Tianbao Yang

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

Scott Pesme · Nicolas Flammarion

Riemannian stochastic optimization methods avoid strict saddle points

Ya-Ping Hsieh · Mohammad Reza Karimi Jaghargh · Andreas Krause · Panayotis Mertikopoulos

Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods

Junchi YANG · Xiang Li · Ilyas Fatkhullin · Niao He

Resilient Constrained Learning

Ignacio Hounie · Alejandro Ribeiro · Luiz F. O. Chamon

Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models

Waïss Azizian · Franck Iutzeler · Jérôme Malick

Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee

Yuanshi Liu · Cong Fang · Tong Zhang

Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise

Ta Duy Nguyen · Thien H Nguyen · Alina Ene · Huy Nguyen

Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms

Qian Yu · Yining Wang · Baihe Huang · Qi Lei · Jason Lee

Macro Placement by Wire-Mask-Guided Black-Box Optimization

Yunqi Shi · Ke Xue · Song Lei · Chao Qian

End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes

Alexandre Maraval · Matthieu Zimmer · Antoine Grosnit · Haitham Bou Ammar

On Masked Pre-training and the Marginal Likelihood

Pablo Moreno-Muñoz · Pol Garcia Recasens · Søren Hauberg

On permutation symmetries in Bayesian neural network posteriors: a variational perspective

Simone Rossi · Simone Rossi · Ankit Singh · Thomas Hannagan

Scaling Laws for Hyperparameter Optimization

Arlind Kadra · Maciej Janowski · Martin Wistuba · Josif Grabocka

Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift

Florian Seligmann · Philipp Becker · Michael Volpp · Gerhard Neumann

Flat Seeking Bayesian Neural Networks

Van-Anh Nguyen · Tung-Long Vuong · Hoang Phan · Thanh-Toan Do · Dinh Phung · Trung Le

Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression

Youngsoo Baek · Samuel Berchuck · Sayan Mukherjee

Soft-Unification in Deep Probabilistic Logic

Jaron Maene · Luc De Raedt

Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis

Victor Letzelter · Mathieu Fontaine · Mickael Chen · Patrick Pérez · Slim Essid · Gaël Richard

Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent

Jihao Andreas Lin · Javier Antorán · Shreyas Padhy · David Janz · José Miguel Hernández-Lobato · Alexander Terenin

GPEX, A Framework For Interpreting Artificial Neural Networks

Amir Hossein Hosseini Akbarnejad · Gilbert Bigras · Nilanjan Ray

Computing Approximate $\ell_p$ Sensitivities

Swati Padmanabhan · David Woodruff · Richard Zhang

Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo

Maxence Noble · Valentin De Bortoli · Alain Durmus

Practical and Asymptotically Exact Conditional Sampling in Diffusion Models

Luhuan Wu · Brian Trippe · Christian Naesseth · David Blei · John Cunningham

Provable convergence guarantees for black-box variational inference

Justin Domke · Robert Gower · Guillaume Garrigos

A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods

Veit David Wild · Sahra Ghalebikesabi · Dino Sejdinovic · Jeremias Knoblauch

NPCL: Neural Processes for Uncertainty-Aware Continual Learning

Saurav Jha · Dong Gong · He Zhao · Lina Yao

Particle-based Variational Inference with Generalized Wasserstein Gradient Flow

Ziheng Cheng · Shiyue Zhang · Longlin Yu · Cheng Zhang

Game Solving with Online Fine-Tuning

Ti-Rong Wu · Hung Guei · Ting Han Wei · Chung-Chin Shih · Jui-Te Chin · I-Chen Wu

Prioritizing Samples in Reinforcement Learning with Reducible Loss

Shivakanth Sujit · Somjit Nath · Pedro Braga · Samira Ebrahimi Kahou

Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games

Youbang Sun · Tao Liu · Ruida Zhou · P. R. Kumar · Shahin Shahrampour

State-Action Similarity-Based Representations for Off-Policy Evaluation

Brahma Pavse · Josiah Hanna

Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning

Riccardo Zamboni · Alberto Maria Metelli · Marcello Restelli

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design

Matthew T Jackson · Minqi Jiang · Jack Parker-Holder · Risto Vuorio · Chris Lu · Greg Farquhar · Shimon Whiteson · Jakob Foerster

Recurrent Hypernetworks are Surprisingly Strong in Meta-RL

Jacob Beck · Risto Vuorio · Zheng Xiong · Shimon Whiteson

H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation

Yanjie Ze · Yanjie Ze · Yuyao Liu · Ruizhe Shi · Jiaxin Qin · Zhecheng Yuan · Jiashun Wang · Huazhe Xu

Gradient Informed Proximal Policy Optimization

Sanghyun Son · Laura Zheng · Ryan Sullivan · Yi-Ling Qiao · Ming Lin

Cross-Domain Policy Adaptation via Value-Guided Data Filtering

Kang Xu · Chenjia Bai · Xiaoteng Ma · Dong Wang · Bin Zhao · Zhen Wang · Xuelong Li · Wei Li

Taylor TD-learning

Michele Garibbo · Maxime Robeyns · Laurence Aitchison

Diffusion Model is an Effective Planner and Data Synthesizer for Multi-Task Reinforcement Learning

Haoran He · Chenjia Bai · Kang Xu · Zhuoran Yang · Weinan Zhang · Dong Wang · Bin Zhao · Xuelong Li

Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off

Zichen (Vincent) Zhang · Johannes Kirschner · Junxi Zhang · Francesco Zanini · Alex Ayoub · Masood Dehghan · Dale Schuurmans

Doubly Robust Augmented Transfer for Meta-Reinforcement Learning

Yuankun Jiang · Nuowen Kan · Chenglin Li · Wenrui Dai · Junni Zou · Hongkai Xiong

Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning

Stephen McAleer · Gabriele Farina · Gaoyue Zhou · Mingzhi Wang · Yaodong Yang · Tuomas Sandholm

Successor-Predecessor Intrinsic Exploration

Changmin Yu · Neil Burgess · Maneesh Sahani · Samuel J Gershman

Distributional Pareto-Optimal Multi-Objective Reinforcement Learning

Xin-Qiang Cai · Pushi Zhang · Li Zhao · Jiang Bian · Masashi Sugiyama · Ashley Llorens

Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation

Wenhao Ding · Laixi Shi · Yuejie Chi · DING ZHAO

Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor

Julien Grand-Clément · Marek Petrik

One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning

Marc Rigter · Marc Rigter · Bruno Lacerda · Nick Hawes

Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage

Masatoshi Uehara · Nathan Kallus · Jason Lee · Wen Sun

Design from Policies: Conservative Test-Time Adaptation for Offline Policy Optimization

Jinxin Liu · Hongyin Zhang · Zifeng Zhuang · Yachen Kang · Donglin Wang · Bin Wang

Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL

Peng Cheng · Xianyuan Zhan · zhihao wu · Wenjia Zhang · Youfang Lin · Shou cheng Song · Han Wang · Li Jiang

VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning

Jiayi Guan · Guang Chen · Jiaming Ji · Long Yang · ao zhou · Zhijun Li · changjun jiang

Supported Value Regularization for Offline Reinforcement Learning

Yixiu Mao · Hongchang Zhang · Chen Chen · Yi Xu · Xiangyang Ji

Adversarial Counterfactual Environment Model Learning

Xiong-Hui Chen · Yang Yu · Zhengmao Zhu · ZhiHua Yu · Chen Zhenjun · Chenghe Wang · Yinan Wu · Rong-Jun Qin · Hongqiu Wu · Ruijin Ding · Huang Fangsheng

Reining Generalization in Offline Reinforcement Learning via Representation Distinction

Yi Ma · Hongyao Tang · Dong Li · Zhaopeng Meng

Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior

Adam Block · Ali Jadbabaie · Daniel Pfrommer · Max Simchowitz · Russ Tedrake

Revisiting the Minimalist Approach to Offline Reinforcement Learning

Denis Tarasov · Vladislav Kurenkov · Alexander Nikulin · Sergey Kolesnikov

Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL

Yang Yue · Rui Lu · Bingyi Kang · Shiji Song · Gao Huang

FlowPG: Action-constrained Policy Gradient with Normalizing Flows

Janaka Brahmanage · Jiajing LING · Akshat Kumar

Flexible Attention-Based Multi-Policy Fusion for Efficient Deep Reinforcement Learning

Zih-Yun Chiu · Yi-Lin Tuan · William Yang Wang · Michael Yip

Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints

Dohyeong Kim · Kyungjae Lee · Songhwai Oh

SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning

Dohyeok Lee · Seungyub Han · Taehyun Cho · Jungwoo Lee

Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL

Chen Sun · Wannan Yang · Thomas Jiralerspong · Dane Malenfant · Benjamin Alsbury-Nealy · Yoshua Bengio · Blake Richards

Thinker: Learning to Plan and Act

Stephen Chung · Ivan Anokhin · David Krueger

ELDEN: Exploration via Local Dependencies

Zizhao Wang · Jiaheng Hu · Peter Stone · Roberto Martín-Martín

PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks

Ian Char · Jeff Schneider

Iterative Reachability Estimation for Safe Reinforcement Learning

Milan Ganai · Zheng Gong · Chenning Yu · Sylvia Herbert · Sicun Gao

Reinforcement Learning with Simple Sequence Priors

Tankred Saanum · Noémi Éltető · Peter Dayan · Marcel Binz · Eric Schulz

Deep Reinforcement Learning with Plasticity Injection

Evgenii Nikishin · Junhyuk Oh · Georg Ostrovski · Clare Lyle · Razvan Pascanu · Will Dabney · Andre Barreto

Active Vision Reinforcement Learning under Limited Visual Observability

Jinghuan Shang · Michael S Ryoo

Inverse Preference Learning: Preference-based RL without a Reward Function

Joey Hejna · Dorsa Sadigh

Diversify \& Conquer: Outcome-directed Curriculum RL via Out-of-Distribution Disagreement

Daesol Cho · Seungjae Lee · H. Jin Kim

Creating Multi-Level Skill Hierarchies in Reinforcement Learning

Joshua B. Evans · Özgür Şimşek

Ess-InfoGAIL: Semi-supervised Imitation Learning from Imbalanced Demonstrations

Huiqiao Fu · Kaiqiang Tang · Yuanyang Lu · Yuanyang Lu · Yiming Qi · Guizhou Deng · Flood Sung · Chunlin Chen

Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning?

Jialu Gao · Kaizhe Hu · Guowei Xu · Huazhe Xu

Optimal Exploration for Model-Based RL in Nonlinear Systems

Andrew Wagenmaker · Guanya Shi · Kevin Jamieson

Inferring the Future by Imagining the Past

Kartik Chandra · Tony Chen · Tzu-Mao Li · Jonathan Ragan-Kelley · Josh Tenenbaum

History Filtering in Imperfect Information Games: Algorithms and Complexity

Christopher Solinas · Doug Rebstock · Nathan Sturtevant · Michael Buro

Emergent Communication for Rules Reasoning

Yuxuan Guo · Yifan Hao · Rui Zhang · Enshuai Zhou · Zidong Du · xishan zhang · Xinkai Song · Yuanbo Wen · Yongwei Zhao · Xuehai Zhou · Jiaming Guo · Qi Yi · Shaohui Peng · Di Huang · Ruizhi Chen · Qi Guo · Yunji Chen

Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity

Weichao Mao · Haoran Qiu · Chen Wang · Hubertus Franke · Zbigniew Kalbarczyk · Ravishankar Iyer · Tamer Basar

AdaPlanner: Adaptive Planning from Feedback with Language Models

Haotian Sun · Yuchen Zhuang · Lingkai Kong · Bo Dai · Chao Zhang

Active Observing in Continuous-time Control

Samuel Holt · Alihan Hüyük · Mihaela van der Schaar

Adaptive Online Replanning with Diffusion Models

Siyuan Zhou · Yilun Du · Shun Zhang · Mengdi Xu · Yikang Shen · Wei Xiao · Dit-Yan Yeung · Chuang Gan

Beyond Average Return in Markov Decision Processes

Alexandre Marthe · Aurélien Garivier · Claire Vernade

Auxiliary Losses for Learning Generalizable Concept-based Models

Ivaxi Sheth · Samira Ebrahimi Kahou

Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases

Mazda Moayeri · Wenxiao Wang · Sahil Singla · Soheil Feizi

Break It Down: Evidence for Structural Compositionality in Neural Networks

Michael Lepori · Thomas Serre · Ellie Pavlick

Labeling Neural Representations with Inverse Recognition

Kirill Bykov · Laura Kopf · Shinichi Nakajima · Marius Kloft · Marina Höhne

How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model

Michael Hanna · Ollie Liu · Alexandre Variengien

Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability

Usha Bhalla · Suraj Srinivas · Himabindu Lakkaraju

Learning Reliable Logical Rules with SATNet

Zhaoyu Li · Jinpei Guo · Yuhe Jiang · Xujie Si

Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities

Dongrui Liu · Huiqi Deng · Xu Cheng · Xu Cheng · Qihan Ren · Kangrui Wang · Quanshi Zhang

SAME: Uncovering GNN Black Box with Structure-aware Shapley-based Multipiece Explanations

Ziyuan Ye · Rihan Huang · Qilin Wu · Quanying Liu

Moral Responsibility for AI Systems

Sander Beckers

Individual Arbitrariness and Group Fairness

Carol Long · Hsiang Hsu · Hsiang Hsu · Wael Alghamdi · Flavio Calmon

BIRD: Generalizable Backdoor Detection and Removal for Deep Reinforcement Learning

Xuan Chen · Wenbo Guo · Wenbo Guo · Guanhong Tao · Xiangyu Zhang · Dawn Song

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

Samuel Dooley · Rhea Sukthanker · John Dickerson · Colin White · Frank Hutter · Micah Goldblum

VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models

Ziyi Yin · Muchao Ye · Tianrong Zhang · Tianyu Du · Tianyu Du · Jinguo Zhu · Han Liu · Jinghui Chen · Ting Wang · Fenglong Ma

Ethical Considerations for Responsible Data Curation

Jerone Andrews · Dora Zhao · William Thong · Apostolos Modas · Orestis Papakyriakopoulos · Alice Xiang

CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference

Wenxuan Zeng · Meng Li · Haichuan Yang · Wen-jie Lu · Runsheng Wang · Ru Huang

Easy Learning from Label Proportions

Róbert Busa-Fekete · Heejin Choi · Travis Dick · Claudio Gentile · Andres Munoz Medina

Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning

Casey Meehan · Florian Bordes · Pascal Vincent · Kamalika Chaudhuri · Chuan Guo

Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation

Wei-Ning Chen · Dan Song · Ayfer Ozgur · Peter Kairouz

Faster Differentially Private Convex Optimization via Second-Order Methods

Arun Ganesh · Mahdi Haghifam · Thomas Steinke · Abhradeep Guha Thakurta

Black-Box Differential Privacy for Interactive ML

Haim Kaplan · Yishay Mansour · Shay Moran · Kobbi Nissim · Uri Stemmer

Unleashing the Power of Randomization in Auditing Differentially Private ML

Krishna Pillutla · Galen Andrew · Peter Kairouz · H. Brendan McMahan · Alina Oprea · Sewoong Oh

Students Parrot Their Teachers: Membership Inference on Model Distillation

Matthew Jagielski · Milad Nasr · Katherine Lee · Christopher A. Choquette-Choo · Nicholas Carlini · Florian Tramer

Private Distribution Learning with Public Data: The View from Sample Compression

Shai Ben-David · Alex Bie · Clément L Canonne · Gautam Kamath · Vikrant Singhal

Eliminating Domain Bias for Federated Learning in Representation Space

Jianqing Zhang · Yang Hua · Jian Cao · Hao Wang · Tao Song · Zhengui XUE · Ruhui Ma · Haibing Guan

Post-processing Private Synthetic Data for Improving Utility on Selected Measures

Hao Wang · Shivchander Sudalairaj · John Henning · Kristjan Greenewald · Akash Srivastava

Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection

Xilie Xu · Jingfeng ZHANG · Feng Liu · Masashi Sugiyama · Mohan Kankanhalli

FedFed: Feature Distillation against Data Heterogeneity in Federated Learning

Zhiqin Yang · Yonggang Zhang · Yu Zheng · Xinmei Tian · Hao Peng · Tongliang Liu · Bo Han

Combating Bilateral Edge Noise for Robust Link Prediction

Zhanke Zhou · Jiangchao Yao · Jiaxu Liu · Xiawei Guo · Quanming Yao · LI He · Liang Wang · Bo Zheng · Bo Han

Use perturbations when learning from explanations

Juyeon Heo · Vihari Piratla · Matthew Wicker · Adrian Weller

Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detection

Yuxin Cao · Yian Li · Yumeng Zhu · Derui Wang · Minhui Xue

Content-based Unrestricted Adversarial Attack

Zhaoyu Chen · Bo Li · Shuang Wu · Kaixun Jiang · Shouhong Ding · Wenqiang Zhang

Class-Conditional Conformal Prediction with Many Classes

Tiffany Ding · Anastasios Angelopoulos · Stephen Bates · Michael Jordan · Ryan Tibshirani

In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer

Yuzhou Cao · Hussein Mozannar · Lei Feng · Hongxin Wei · Bo An

Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses

Gon Buzaglo · Niv Haim · Gilad Yehudai · Gal Vardi · Yakir Oz · Yaniv Nikankin · Michal Irani

Regression with Cost-based Rejection

Xin Cheng · Yuzhou Cao · Haobo Wang · Hongxin Wei · Bo An · Lei Feng

Derandomized novelty detection with FDR control via conformal e-values

Meshi Bashari · Amir Epstein · Yaniv Romano · Matteo Sesia

Fast Partitioned Learned Bloom Filter

Atsuki Sato · Yusuke Matsui

Minimum-Risk Recalibration of Classifiers

Zeyu Sun · Dogyoon Song · Alfred Hero

On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions

Yufeng Zhang · Jialu Pan · Li Ken Li · Wanwei Liu · Zhenbang Chen · Xinwang Liu · J Wang

Not All Out-of-Distribution Data Are Harmful to Open-Set Active Learning

Yang Yang · Yuxuan Zhang · XIN SONG · Yi Xu

Learning List-Level Domain-Invariant Representations for Ranking

Ruicheng Xian · Honglei Zhuang · Zhen Qin · Hamed Zamani · Jing Lu · Ji Ma · Kai Hui · Han Zhao · Xuanhui Wang · Michael Bendersky

Creating a Public Repository for Joining Private Data

James Cook · Milind Shyani · Nina Mishra

Structure of universal formulas

Dmitry Yarotsky

Incentivizing Honesty among Competitors in Collaborative Learning and Optimization

Florian E. Dorner · Nikola Konstantinov · Georgi Pashaliev · Martin Vechev

Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents

Nika Haghtalab · Chara Podimata · Kunhe Yang

Regret Matching+: (In)Stability and Fast Convergence in Games

Gabriele Farina · Julien Grand-Clément · Christian Kroer · Chung-Wei Lee · Haipeng Luo

Computing Optimal Nash Equilibria in Multiplayer Games

Youzhi Zhang · Bo An · Venkatramanan Subrahmanian · Venkatramanan Subrahmanian

On the Robustness of Mechanism Design under Total Variation Distance

Anuran Makur · Marios Mertzanidis · Alexandros Psomas · Athina Terzoglou

Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling

Yoav Kolumbus · Menahem Levy · Noam Nisan

Similarity-based cooperative equilibrium

Caspar Oesterheld · Johannes Treutlein · Roger Grosse · Vincent Conitzer · Jakob Foerster

Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression

Ilias Diakonikolas · Daniel Kane · Ankit Pensia · Ankit Pensia · Thanasis Pittas

Efficient Testable Learning of Halfspaces with Adversarial Label Noise

Ilias Diakonikolas · Daniel Kane · Vasilis Kontonis · Sihan Liu · Nikos Zarifis

Robust Mean Estimation Without Moments for Symmetric Distributions

Gleb Novikov · David Steurer · Stefan Tiegel

Learning with Explanation Constraints

Rattana Pukdee · Dylan Sam · J. Zico Kolter · Maria-Florina Balcan · Pradeep Ravikumar

Optimistic Rates for Multi-Task Representation Learning

Austin Watkins · Enayat Ullah · Thanh Nguyen-Tang · Raman Arora

$H$-Consistency Bounds: Characterization and Extensions

Anqi Mao · Mehryar Mohri · Yutao Zhong

Robust Matrix Sensing in the Semi-Random Model

Xing Gao · Yu Cheng

Demystifying the Optimal Performance of Multi-Class Classification

Minoh Jeong · Martina Cardone · Alex Dytso

On Certified Generalization in Structured Prediction

Bastian Boll · Christoph Schnörr

Error Bounds for Learning with Vector-Valued Random Features

Samuel Lanthaler · Nicholas H. Nelsen

A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression

Tin Sum Cheng · Aurelien Lucchi · Anastasis Kratsios · Ivan Dokmanić · David Belius

On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences

Alireza F. Pour · Hassan Ashtiani

Initialization-Dependent Sample Complexity of Linear Predictors and Neural Networks

Roey Magen · Ohad Shamir

Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds

Ziqiao Wang · Yongyi Mao

An Adaptive Algorithm for Learning with Unknown Distribution Drift

Alessio Mazzetto · Eli Upfal

Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach

Urte Adomaityte · Gabriele Sicuro · Pierpaolo Vivo

Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond $1+\alpha$ Moments

Trung Dang · Jasper Lee · Maoyuan 'Raymond' Song · Paul Valiant

Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method

Constantine Caramanis · Dimitris Fotakis · Alkis Kalavasis · Vasilis Kontonis · Christos Tzamos

Near-optimal learning with average Hölder smoothness

Guy Kornowski · Steve Hanneke · Aryeh Kontorovich

When are ensembles really effective?

Ryan Theisen · Hyunsuk Kim · Yaoqing Yang · Liam Hodgkinson · Michael Mahoney

Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits

Haolin Liu · Chen-Yu Wei · Julian Zimmert

Unconstrained Dynamic Regret via Sparse Coding

Zhiyu Zhang · Zhiyu Zhang · Ashok Cutkosky · Yannis Paschalidis

Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts

Chaoqi Wang · Ziyu Ye · Zhe Feng · Ashwinkumar Badanidiyuru Varadaraja · Haifeng Xu

An active learning framework for multi-group mean estimation

Abdellah Aznag · Rachel Cummings · Adam N. Elmachtoub

A Trichotomy for Transductive Online Learning

Steve Hanneke · Shay Moran · Jonathan Shafer

Best Arm Identification with Fixed Budget: A Large Deviation Perspective

Po-An Wang · Ruo-Chun Tzeng · Alexandre Proutiere

Understanding Multi-phase Optimization Dynamics and Rich Nonlinear Behaviors of ReLU Networks

Mingze Wang · Chao Ma

Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm

Miaoxi Zhu · Li Shen · Bo Du · Dacheng Tao

Parallel Submodular Function Minimization

Deeparnab Chakrabarty · Andrei Graur · Haotian Jiang · Aaron Sidford

Composable Coresets for Determinant Maximization: Greedy is Almost Optimal

Siddharth Gollapudi · Sepideh Mahabadi · Varun Sivashankar

Linear Time Algorithms for k-means with Multi-Swap Local Search

Junyu Huang · Qilong Feng · Ziyun Huang · Jinhui Xu · Jianxin Wang

Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization

Daesung Kim · Hye Won Chung

Lookaround Optimizer: $k$ steps around, 1 step average

Jiangtao Zhang · Shunyu Liu · Jie Song · Tongtian Zhu · Zhengqi Xu · Mingli Song

Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming

Gregory Dexter · Petros Drineas · David Woodruff · Taisuke Yasuda

Label Correction of Crowdsourced Noisy Annotations with an Instance-Dependent Noise Transition Model

Hui GUO · Boyu Wang · Grace Yi

Generalized Belief Transport

Junqi Wang · PEI WANG · Patrick Shafto

On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis

Arghya Datta · Sayak Chakrabarty

Conformal PID Control for Time Series Prediction

Anastasios Angelopoulos · Emmanuel Candes · Ryan Tibshirani

Self-Predictive Universal AI

Elliot Catt · Jordi Grau-Moya · Marcus Hutter · Matthew Aitchison · Tim Genewein · Grégoire Delétang · Kevin Li · Joel Veness

Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time

Xiang Ji · Gen Li

Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds

Jiayi Huang · Han Zhong · Liwei Wang · Lin Yang

Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability

Hanlin Zhu · Amy Zhang

Finding Safe Zones of Markov Decision Processes Policies

Lee Cohen · Yishay Mansour · Michal Moshkovitz

Tempo Adaptation in Non-stationary Reinforcement Learning

Hyunin Lee · Yuhao Ding · Jongmin Lee · Ming Jin · Javad Lavaei · Somayeh Sojoudi

FIND: A Function Description Benchmark for Evaluating Interpretability Methods

Sarah Schwettmann · Tamar Shaham · Joanna Materzynska · Neil Chowdhury · Shuang Li · Jacob Andreas · David Bau · Antonio Torralba

Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes

Cai Zhou · Xiyuan Wang · Muhan Zhang

Worst-case Performance of Popular Approximate Nearest Neighbor Search Implementations: Guarantees and Limitations

Piotr Indyk · Haike Xu

Streaming Algorithms and Lower Bounds for Estimating Correlation Clustering Cost

Sepehr Assadi · Vihan Shah · Chen Wang

Variational Gaussian Processes with Decoupled Conditionals

Xinran Zhu · Kaiwen Wu · Natalie Maus · Jacob Gardner · David Bindel

Memory-Constrained Algorithms for Convex Optimization

Moise Blanchard · Junhui Zhang · Patrick Jaillet

Collaborative Alignment of NLP Models

Fereshte Khani · Marco Tulio Ribeiro

Coherent Soft Imitation Learning

Joe Watson · Sandy Huang · Nicolas Heess

Lower Bounds on Adaptive Sensing for Matrix Recovery

Praneeth Kacham · David Woodruff

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions

Abhineet Agarwal · Anish Agarwal · Suhas Vijaykumar

Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data

Ruiqi Zhang · Andrea Zanette

Large Language Models Are Zero-Shot Time Series Forecasters

Nate Gruver · Marc Finzi · Shikai Qiu · Andrew Wilson

Rubik's Cube: High-Order Channel Interactions with a Hierarchical Receptive Field

Naishan Zheng · man zhou · Chong Zhou · Chen Change Loy

Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction

Souhaib Attaiki · Maks Ovsjanikov

Text-to-Image Diffusion Models are Zero Shot Classifiers

Kevin Clark · Priyank Jaini

Equivariant Adaptation of Large Pretrained Models

Arnab Kumar Mondal · Siba Smarak Panigrahi · Oumar Kaba · Sai Rajeswar Mudumba · Siamak Ravanbakhsh

Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple!

Konstantin Makarychev · Sayak Chakrabarty

Projection-Free Online Convex Optimization via Efficient Newton Iterations

Khashayar Gatmiry · Zak Mhammedi

Lift Yourself Up: Retrieval-augmented Text Generation with Self-Memory

Xin Cheng · Di Luo · Xiuying Chen · Lemao Liu · Dongyan Zhao · Rui Yan

Masked Space-Time Hash Encoding for Efficient Dynamic Scene Reconstruction

Feng Wang · Zilong Chen · Guokang Wang · Yafei Song · Huaping Liu

SQ Lower Bounds for Learning Mixtures of Linear Classifiers

Ilias Diakonikolas · Daniel Kane · Yuxin Sun

Learning To Dive In Branch And Bound

Max Paulus · Andreas Krause

Strategyproof Voting under Correlated Beliefs

Daniel Halpern · Rachel Li · Ariel Procaccia

Learning to Influence Human Behavior with Offline Reinforcement Learning

Joey Hong · Sergey Levine · Anca Dragan

A Fractional Graph Laplacian Approach to Oversmoothing

Sohir Maskey · Raffaele Paolino · Aras Bacho · Gitta Kutyniok

Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language.

Eghbal Hosseini · Evelina Fedorenko

Model Spider: Learning to Rank Pre-Trained Models Efficiently

Yi-Kai Zhang · Ting-Ji Huang · Yao-Xiang Ding · De-Chuan Zhan · Han-Jia Ye

Directional diffusion models for graph representation learning

Run Yang · Yuling Yang · Fan Zhou · Qiang Sun

AIMS: All-Inclusive Multi-Level Segmentation for Anything

Lu Qi · Jason Kuen · Weidong Guo · Jiuxiang Gu · Zhe Lin · Bo Du · Yu Xu · Ming-Hsuan Yang

Triple Eagle: Simple, Fast and Practical Budget-Feasible Mechanisms

Kai Han · You Wu · He Huang · Shuang Cui

Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation

Yuxuan Song · Jingjing Gong · Minkai Xu · Ziyao Cao · Yanyan Lan · Stefano Ermon · Hao Zhou · Wei-Ying Ma

Simplifying Neural Network Training Under Class Imbalance

Ravid Shwartz-Ziv · Micah Goldblum · Yucen Li · C. Bayan Bruss · Andrew Wilson

Graph-Structured Gaussian Processes for Transferable Graph Learning

Jun Wu · Lisa Ainsworth · Andrew Leakey · Haixun Wang · Jingrui He

Learning Modulated Transformation in GANs

Ceyuan Yang · Qihang Zhang · Yinghao Xu · Jiapeng Zhu · Yujun Shen · Bo Dai

Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost

Yu-Jie Zhang · Masashi Sugiyama

Sample based Explanations via Generalized Representers

Che-Ping Tsai · Chih-Kuan Yeh · Pradeep Ravikumar

A Unified Model and Dimension for Interactive Estimation

Nataly Brukhim · Miro Dudik · Aldo Pacchiano · Robert Schapire

VaRT: Variational Regression Trees

Sebastian Salazar

Parameter-efficient Tuning of Large-scale Multimodal Foundation Model

Haixin Wang · Xinlong Yang · Jianlong Chang · Dian Jin · Jinan Sun · Shikun Zhang · Xiao Luo · Qi Tian

Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer

Yuandong Tian · Yiping Wang · Beidi Chen · Simon Du

Multi-Head Adapter Routing for Cross-Task Generalization

Lucas Page-Caccia · Edoardo Maria Ponti · Zhan Su · Matheus Pereira · Nicolas Le Roux · Alessandro Sordoni

Symbolic Discovery of Optimization Algorithms

Xiangning Chen · Chen Liang · Da Huang · Esteban Real · Kaiyuan Wang · Hieu Pham · Xuanyi Dong · Thang Luong · Cho-Jui Hsieh · Yifeng Lu · Quoc V Le

Causal Discovery from Subsampled Time Series with Proxy Variables

Mingzhou Liu · Xinwei Sun · Lingjing Hu · Yizhou Wang

Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$-Differential Privacy

Chendi Wang · Buxin Su · Jiayuan Ye · Reza Shokri · Weijie Su

A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games

Zaiwei Chen · Kaiqing Zhang · Eric Mazumdar · Asuman Ozdaglar · Adam Wierman

Learning Cuts via Enumeration Oracles

Daniel Thuerck · Boro Sofranac · Marc E Pfetsch · Sebastian Pokutta

RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths

Zeyue Xue · Guanglu Song · Qiushan Guo · Boxiao Liu · Zhuofan Zong · Yu Liu · Ping Luo

Partial Matrix Completion

Elad Hazan · Adam Tauman Kalai · Varun Kanade · Clara Mohri · Y. Jennifer Sun

The Rise of AI Language Pathologists: Exploring Two-level Prompt Learning for Few-shot Weakly-supervised Whole Slide Image Classification

Linhao Qu · xiaoyuan luo · Kexue Fu · Manning Wang · Zhijian Song

Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task

Maya Okawa · Ekdeep S Lubana · Robert Dick · Hidenori Tanaka

Affinity-Aware Graph Networks

Ameya Velingker · Ali Sinop · Ira Ktena · Petar Veličković · Sreenivas Gollapudi

TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter

Yiqun Chen · James Zou

Information Theoretic Lower Bounds for Information Theoretic Upper Bounds

Roi Livni

Efficient Neural Music Generation

Max W. Y. Lam · Qiao Tian · Tang Li · Zongyu Yin · Siyuan Feng · Ming Tu · Yuliang Ji · Rui Xia · Mingbo Ma · Xuchen Song · Jitong Chen · Wang Yuping · Yuxuan Wang

DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis

Youngjoong Kwon · Lingjie Liu · Henry Fuchs · Marc Habermann · Christian Theobalt

Learning to Compress Prompts with Gist Tokens

Jesse Mu · Xiang Li · Noah Goodman

Go to Event Page

Creative AI Session 3

Jean Oh · Isabelle Guyon

10:45 AM - 2:15 PM

8 Events in this session

Archi Guesser - An AI Art Architecture Educational Game

Collaborative Synthscapes from Words

Creating Playful Comics Together with AI

Q's Views #1-#3 (+1)

Resonator: An AI-assisted Musical Experience for Human Connection

salad bowl

NeuroView: Generative Visualization of the Diversity of Brain Responses to Jazz

Fusion: Landscape and Beyond

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Invited Talk

Online Reinforcement Learning in Digital Health Interventions

Susan Murphy

2:15 PM - 3:05 PM

In this talk I will discuss first solutions to some of the challenges we face in developing online RL algorithms for use in digital health interventions targeting patients struggling with health problems such as substance misuse, hypertension and bone marrow transplantation. Digital health raises a number of challenges to the RL community including different sets of actions, each set intended to impact patients over a different time scale; the need to learn both within an implementation and between implementations of the RL algorithm; noisy environments and a lack of mechanistic models. In all of these settings the online line algorithm must be stable and autonomous. Despite these challenges, RL, with careful initialization, with careful management of bias/variance tradeoff and by close collaboration with health scientists can be successful. We can make an impact!

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Speaker Bio

Susan A. Murphy is Professor of Statistics and Computer Science at Harvard University. Her research focuses on improving sequential decision making in health, in particular the development of online, real-time reinforcement learning algorithms for use in personalized digital health. She is a member of the US National Academy of Sciences and of the US National Academy of Medicine. In 2013 she was awarded a MacArthur Fellowship for her work on experimental designs to inform sequential decision making. She is a Fellow of the College on Problems in Drug Dependence, Past-President of Institute of Mathematical Statistics, and a former editor of the Annals of Statistics.

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Oral

Oral 6D Theory

3:20 PM - 4:20 PM

4 Events in this session

Optimal Learners for Realizable Regression: PAC Learning and Online Learning

Idan Attias · Steve Hanneke · Alkis Kalavasis · Amin Karbasi · Grigoris Velegkas

Random Cuts are Optimal for Explainable k-Medians

Konstantin Makarychev · Liren Shan

Tester-Learners for Halfspaces: Universal Algorithms

Aravind Gollakota · Adam Klivans · Konstantinos Stavropoulos · Arsen Vasilyan

Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures

Hamish Flynn · David Reeb · Melih Kandemir · Jan Peters

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Oral

Oral 6A LLMs

3:20 PM - 4:20 PM

4 Events in this session

Are Emergent Abilities of Large Language Models a Mirage?

Rylan Schaeffer · Brando Miranda · Sanmi Koyejo

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models

Guillermo Ortiz-Jimenez · Alessandro Favero · Pascal Frossard

The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks

Ziqian Zhong · Ziming Liu · Max Tegmark · Jacob Andreas

Jailbroken: How Does LLM Safety Training Fail?

Alexander Wei · Nika Haghtalab · Jacob Steinhardt

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Oral

Oral 6B RL

3:20 PM - 4:20 PM

4 Events in this session

When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment

Tianwei Ni · Michel Ma · Benjamin Eysenbach · Pierre-Luc Bacon

Bridging RL Theory and Practice with the Effective Horizon

Cassidy Laidlaw · Stuart J Russell · Anca Dragan

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn

MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning

Zeyuan Ma · Hongshu Guo · Jiacheng Chen · Zhenrui Li · Guojun Peng · Yue-Jiao Gong · Yining Ma · Zhiguang Cao

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Oral

Oral 6C Vision

3:20 PM - 4:20 PM

4 Events in this session

Siamese Masked Autoencoders

Agrim Gupta · Jiajun Wu · Jia Deng · Fei-Fei Li

Image Captioners Are Scalable Vision Learners Too

Michael Tschannen · Manoj Kumar · Andreas Steiner · Andreas Steiner · Xiaohua Zhai · Neil Houlsby · Lucas Beyer

The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation

Saurabh Saxena · Charles Herrmann · Junhwa Hur · Abhishek Kar · Mohammad Norouzi · Deqing Sun · David Fleet

Spatial-frequency channels, shape bias, and adversarial robustness

Ajay Subramanian · Elena Sizikova · Najib Majaj · Denis Pelli

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Poster

Poster Session 6

5:00 PM - 7:00 PM

574 Events in this session

Sample-efficient Multi-objective Molecular Optimization with GFlowNets

Yiheng Zhu · Jialu Wu · Chaowen Hu · Jiahuan Yan · kim hsieh · Tingjun Hou · Jian Wu

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design

AkshatKumar Nigam · Robert Pollice · Gary Tom · Kjell Jorner · John Willes · Luca Thiede · Anshul Kundaje · Alan Aspuru-Guzik

Graph Denoising Diffusion for Inverse Protein Folding

Kai Yi · Bingxin Zhou · Yiqing Shen · Yiqing Shen · Pietro Lió · Yuguang Wang

Uncovering Neural Scaling Laws in Molecular Representation Learning

Dingshuo Chen · Yanqiao Zhu · Jieyu Zhang · Yuanqi Du · Zhixun Li · Qiang Liu · Shu Wu · Liang Wang

ProteinShake: Building datasets and benchmarks for deep learning on protein structures

Tim Kucera · Carlos Oliver · Dexiong Chen · Karsten Borgwardt

Lo-Hi: Practical ML Drug Discovery Benchmark

Simon Steshin

GAUCHE: A Library for Gaussian Processes in Chemistry

Ryan-Rhys Griffiths · Leo Klarner · Henry Moss · Aditya Ravuri · Sang Truong · Yuanqi Du · Samuel Stanton · Gary Tom · Bojana Rankovic · Arian Jamasb · Arian Jamasb · Aryan Deshwal · Julius Schwartz · Austin Tripp · Gregory Kell · Simon Frieder · Anthony Bourached · Alex Chan · Jacob Moss · Chengzhi Guo · Johannes Peter Dürholt · Saudamini Chaurasia · Ji Won Park · Felix Strieth-Kalthoff · Alpha Lee · Bingqing Cheng · Alan Aspuru-Guzik · Philippe Schwaller · Jian Tang

Benchmark of Machine Learning Force Fields for Semiconductor Simulations: Datasets, Metrics, and Comparative Analysis

Geonu Kim · Byunggook Na · Gunhee Kim · Hyuntae Cho · Seungjin Kang · Hee Sun Lee · Saerom Choi · Heejae Kim · Seungwon Lee · Yongdeok Kim

DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing

Yangtian Zhang · Zuobai Zhang · Bozitao Zhong · Bozitao Zhong · Sanchit Misra · Jian Tang

What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks

Taicheng Guo · kehan Guo · Bozhao Nan · Zhenwen Liang · Zhichun Guo · Nitesh Chawla · Olaf Wiest · Xiangliang Zhang

WildfireSpreadTS: A dataset of multi-modal time series for wildfire spread prediction

Sebastian Gerard · Yu Zhao · Josephine Sullivan

ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling

Tung Nguyen · Jason Jewik · Hritik Bansal · Prakhar Sharma · Aditya Grover

SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data

Mélisande Teng · Amna Elmustafa · Benjamin Akera · Yoshua Bengio · Hager Radi · Hugo Larochelle · David Rolnick

Digital Typhoon: Long-term Satellite Image Dataset for the Spatio-Temporal Modeling of Tropical Cyclones

Asanobu Kitamoto · Jared Hwang · Bastien Vuillod · Lucas Gautier · Yingtao Tian · Tarin Clanuwat

BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series

Andrea Nascetti · Ritu Yadav · Kirill Brodt · Qixun Qu · Hongwei Fan · Yuri Shendryk · Isha Shah · Christine Chung

FLAIR : a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery

Anatol Garioud · Nicolas Gonthier · Loic Landrieu · Apolline De Wit · Marion Valette · Marc Poupée · Sebastien Giordano · boris Wattrelos

STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events

Kazuki Shimada · Archontis Politis · Parthasaarathy Sudarsanam · Daniel A. Krause · Kengo Uchida · Sharath Adavanne · Aapo Hakala · Yuichiro Koyama · Naoya Takahashi · Shusuke Takahashi · Tuomas Virtanen · Yuki Mitsufuji

Learning Human Action Recognition Representations Without Real Humans

Howard Zhong · Samarth Mishra · Donghyun Kim · SouYoung Jin · Rameswar Panda · Hilde Kuehne · Leonid Karlinsky · Venkatesh Saligrama · Aude Oliva · Rogerio Feris

MiliPoint: A Point Cloud Dataset for mmWave Radar

Han Cui · Shu Zhong · Jiacheng Wu · Zichao Shen · Naim Dahnoun · Yiren Zhao

EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset

Hao Tang · Kevin J Liang · Kristen Grauman · Matt Feiszli · Weiyao Wang

Real-World Image Variation by Aligning Diffusion Inversion Chain

Yuechen Zhang · Jinbo Xing · Eric Lo · Jiaya Jia

trajdata: A Unified Interface to Multiple Human Trajectory Datasets

Boris Ivanovic · Guanyu Song · Igor Gilitschenski · Marco Pavone

FORB: A Flat Object Retrieval Benchmark for Universal Image Embedding

Pengxiang Wu · Siman Wang · Kevin Dela Rosa · Derek Hu

D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts

Fenggen Yu · Qimin Chen · Maham Tanveer · Ali Mahdavi Amiri · Hao Zhang

CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation

Xiuzhe Wu · Peng Dai · Weipeng DENG · Handi Chen · Yang Wu · Yan-Pei Cao · Ying Shan · Xiaojuan Qi

MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion

Shitao Tang · Fuyang Zhang · Jiacheng Chen · Peng Wang · Yasutaka Furukawa

InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion

Fangzhou Lin · Yun Yue · Ziming Zhang · Songlin Hou · Kazunori Yamada · Vijaya Kolachalama · Venkatesh Saligrama

H2RBox-v2: Incorporating Symmetry for Boosting Horizontal Box Supervised Oriented Object Detection

Yi Yu · Xue Yang · Xue Yang · Qingyun Li · Yue Zhou · Feipeng Da · Junchi Yan

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union

Zifu Wang · Maxim Berman · Amal Rannen-Triki · Philip Torr · Devis Tuia · Tinne Tuytelaars · Luc V Gool · Jiaqian Yu · Matthew Blaschko

UDC-SIT: A Real-World Dataset for Under-Display Cameras

Kyusu Ahn · Byeonghyun Ko · HyunGyu Lee · Chanwoo Park · Jaejin Lee

WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes

Satoshi Tsutsui · Winnie Pang · Bihan Wen

Learning to Taste: A Multimodal Wine Dataset

Thoranna Bender · Simon Sørensen · Alireza Kashani · Kristjan Eldjarn Hjorleifsson · Grethe Hyldig · Søren Hauberg · Serge Belongie · Frederik Warburg

OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents

Hugo Laurençon · Lucile Saulnier · Leo Tronchon · Stas Bekman · Amanpreet Singh · Anton Lozhkov · Thomas Wang · Siddharth Karamcheti · Alexander Rush · Douwe Kiela · Matthieu Cord · Victor Sanh

VidChapters-7M: Video Chapters at Scale

Antoine Yang · Arsha Nagrani · Ivan Laptev · Josef Sivic · Cordelia Schmid

Scalable 3D Captioning with Pretrained Models

Tiange Luo · Chris Rockwell · Honglak Lee · Justin Johnson

A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset

Zahra Gharaee · ZeMing Gong · Nicholas Pellegrino · Iuliia Zarubiieva · Joakim Bruslund Haurum · Scott Lowe · Jaclyn McKeown · Chris Ho · Joschka McLeod · Yi-Yun Wei · Jireh Agda · Sujeevan Ratnasingham · Dirk Steinke · Angel Chang · Graham Taylor · Paul Fieguth

Diverse Shape Completion via Style Modulated Generative Adversarial Networks

Wesley Khademi · Fuxin Li

Image Captioners Are Scalable Vision Learners Too

Michael Tschannen · Manoj Kumar · Andreas Steiner · Andreas Steiner · Xiaohua Zhai · Neil Houlsby · Lucas Beyer

Robust Model Reasoning and Fitting via Dual Sparsity Pursuit

Xingyu Jiang · Jiayi Ma

NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations

Varun Jampani · Kevis-kokitsi Maninis · Andreas Engelhardt · Arjun Karpur · Karen Truong · Kyle Sargent · Stefan Popov · Andre Araujo · Ricardo Martin Brualla · Kaushal Patel · Daniel Vlasic · Vittorio Ferrari · Ameesh Makadia · Ce Liu · Yuanzhen Li · Howard Zhou

PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection

Qiang Zhou · Weize Li · Lihan Jiang · Guoliang Wang · Guyue Zhou · Shanghang Zhang · Hao Zhao

TOA: Task-oriented Active VQA

xiaoying xing · Mingfu Liang · Ying Wu

OBJECT 3DIT: Language-guided 3D-aware Image Editing

Oscar Michel · Anand Bhattad · Eli VanderBilt · Ranjay Krishna · Aniruddha Kembhavi · Tanmay Gupta

PGDiff: Guiding Diffusion Models for Versatile Face Restoration via Partial Guidance

Peiqing Yang · Shangchen Zhou · Qingyi Tao · Chen Change Loy

A Dataset of Relighted 3D Interacting Hands

Gyeongsik Moon · Shunsuke Saito · Weipeng Xu · Rohan Joshi · Julia Buffalini · Harley Bellan · Nicholas Rosen · Jesse Richardson · Mallorie Mize · Philippe De Bree · Tomas Simon · Bo Peng · Shubham Garg · Kevyn McPhail · Takaaki Shiratori

AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesis

Susan Liang · Chao Huang · Yapeng Tian · Anurag Kumar · Chenliang Xu

Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving

Xiaoyu Tian · Tao Jiang · Longfei Yun · Yucheng Mao · Huitong Yang · Yue Wang · Yilun Wang · Hang Zhao

MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing

Kai Zhang · Lingbo Mo · Wenhu Chen · Huan Sun · Yu Su

Humans in Kitchens: A Dataset for Multi-Person Human Motion Forecasting with Scene Context

Julian Tanke · Oh-Hun Kwon · Felix B Mueller · Andreas Doering · Jürgen Gall

EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding

Karttikeya Mangalam · Raiymbek Akshulakov · Jitendra Malik

MM-Fi: Multi-Modal Non-Intrusive 4D Human Dataset for Versatile Wireless Sensing

Jianfei Yang · He Huang · Yunjiao Zhou · Xinyan Chen · Yuecong Xu · Shenghai Yuan · Han Zou · Chris Xiaoxuan Lu · Lihua Xie

SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model

Di Wang · Jing Zhang · Bo Du · Minqiang Xu · Lin Liu · Dacheng Tao · Liangpei Zhang

GEO-Bench: Toward Foundation Models for Earth Monitoring

Alexandre Lacoste · Nils Lehmann · Pau Rodriguez · Evan Sherwin · Hannah Kerner · Björn Lütjens · Jeremy Irvin · David Dao · Hamed Alemohammad · Alexandre Drouin · Mehmet Gunturkun · Gabriel Huang · David Vazquez · Dava Newman · Yoshua Bengio · Stefano Ermon · Xiaoxiang Zhu

Auslan-Daily: Australian Sign Language Translation for Daily Communication and News

Xin Shen · Shaozu Yuan · Hongwei Sheng · Heming Du · Xin Yu

Perception Test: A Diagnostic Benchmark for Multimodal Video Models

Viorica Patraucean · Lucas Smaira · Ankush Gupta · Adria Recasens · Larisa Markeeva · Dylan Banarse · Skanda Koppula · joseph heyward · Mateusz Malinowski · Yi Yang · Carl Doersch · Tatiana Matejovicova · Yury Sulsky · Antoine Miech · Alexandre Fréchette · Hanna Klimczak · Raphael Koster · Junlin Zhang · Stephanie Winkler · Yusuf Aytar · Simon Osindero · Dima Damen · Andrew Zisserman · Joao Carreira

ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image Classification

Mohammad Reza Taesiri · Giang Nguyen · Sarra Habchi · Cor-Paul Bezemer · Anh Nguyen

Estimating Generic 3D Room Structures from 2D Annotations

Denys Rozumnyi · Stefan Popov · Kevis-kokitsi Maninis · Matthias Niessner · Vittorio Ferrari

The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation

Saurabh Saxena · Charles Herrmann · Junhwa Hur · Abhishek Kar · Mohammad Norouzi · Deqing Sun · David Fleet

OV-PARTS: Towards Open-Vocabulary Part Segmentation

Meng Wei · Xiaoyu Yue · Wenwei Zhang · Shu Kong · Xihui Liu · Jiangmiao Pang

Language-driven Scene Synthesis using Multi-conditional Diffusion Model

An Dinh Vuong · Minh Nhat VU · Toan Nguyen · Baoru Huang · Dzung Nguyen · Thieu Vo · Anh Nguyen

Seeing is not always believing: Benchmarking Human and Model Perception of AI-Generated Images

Zeyu Lu · Di Huang · LEI BAI · Jingjing Qu · Chengyue Wu · Xihui Liu · Wanli Ouyang

Temporal Continual Learning with Prior Compensation for Human Motion Prediction

Jianwei Tang · Jiangxin Sun · Xiaotong Lin · lifang zhang · Wei-Shi Zheng · Jian-Fang Hu

Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models

Gen Luo · Yiyi Zhou · Tianhe Ren · Shengxin Chen · Xiaoshuai Sun · Rongrong Ji

Modeling Human Visual Motion Processing with Trainable Motion Energy Sensing and a Self-attention Network

Zitang Sun · Yen-Ju Chen · Yung-Hao Yang · Shin'ya Nishida

FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning

Kun Song · Huimin Ma · Bochao Zou · Huishuai Zhang · Weiran Huang

SODA: Robust Training of Test-Time Data Adaptors

Zige Wang · Yonggang Zhang · Zhen Fang · Long Lan · Wenjing Yang · Bo Han

The Drunkard’s Odometry: Estimating Camera Motion in Deforming Scenes

David Recasens Lafuente · Martin R. Oswald · Marc Pollefeys · Javier Civera

EPIC Fields: Marrying 3D Geometry and Video Understanding

Vadim Tschernezki · Ahmad Darkhalil · Zhifan Zhu · David Fouhey · Iro Laina · Diane Larlus · Dima Damen · Andrea Vedaldi

Described Object Detection: Liberating Object Detection with Flexible Expressions

Chi Xie · Zhao Zhang · Yixuan Wu · Feng Zhu · Rui Zhao · Shuang Liang

All Points Matter: Entropy-Regularized Distribution Alignment for Weakly-supervised 3D Segmentation

Liyao Tang · Zhe Chen · Shanshan Zhao · Chaoyue Wang · Dacheng Tao

Motion-X: A Large-scale 3D Expressive Whole-body Human Motion Dataset

Jing Lin · Ailing Zeng · Shunlin Lu · Yuanhao Cai · Ruimao Zhang · Haoqian Wang · Lei Zhang

Object Reprojection Error (ORE): Camera pose benchmarks from lightweight tracking annotations

Xingyu Chen · Weiyao Wang · Hao Tang · Matt Feiszli

Objaverse-XL: A Universe of 10M+ 3D Objects

Matt Deitke · Ruoshi Liu · Matthew Wallingford · Huong Ngo · Oscar Michel · Aditya Kusupati · Alan Fan · Christian Laforte · Vikram Voleti · Samir Yitzhak Gadre · Eli VanderBilt · Aniruddha Kembhavi · Carl Vondrick · Georgia Gkioxari · Kiana Ehsani · Ludwig Schmidt · Ali Farhadi

Compact Neural Volumetric Video Representations with Dynamic Codebooks

Haoyu Guo · Sida Peng · Yunzhi Yan · Linzhan Mou · Yujun Shen · Hujun Bao · Xiaowei Zhou

Ego4D Goal-Step: Toward Hierarchical Understanding of Procedural Activities

Yale Song · Eugene Byrne · Tushar Nagarajan · Huiyu Wang · Miguel Martin · Lorenzo Torresani

Emergent Communication in Interactive Sketch Question Answering

Zixing Lei · Yiming Zhang · Yuxin Xiong · Siheng Chen

TransHP: Image Classification with Hierarchical Prompting

Wenhao Wang · Yifan Sun · Wei Li · Yi Yang

AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator

Elysia Smyers · Sydney Katz · Anthony Corso · Mykel J Kochenderfer

OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping

Huijie Wang · Tianyu Li · Yang Li · Li Chen · Chonghao Sima · Zhenbo Liu · Bangjun Wang · Peijin Jia · Yuting Wang · Shengyin Jiang · Feng Wen · Hang Xu · Ping Luo · Junchi Yan · Wei Zhang · Hongyang Li

Visual Programming for Step-by-Step Text-to-Image Generation and Evaluation

Jaemin Cho · Abhay Zala · Mohit Bansal

LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark

Zhenfei Yin · Jiong Wang · Jianjian Cao · Zhelun Shi · Dingning Liu · Mukai Li · Xiaoshui Huang · Zhiyong Wang · Lu Sheng · LEI BAI · Jing Shao · Wanli Ouyang

E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning

Xiuhong Lin · Changjie Qiu · zhipeng cai · Siqi Shen · Yu Zang · Weiquan Liu · Xuesheng Bian · Matthias Müller · Cheng Wang

CycleNet: Rethinking Cycle Consistency in Text-Guided Diffusion for Image Manipulation

Sihan Xu · Ziqiao Ma · Yidong Huang · Honglak Lee · Joyce Chai

Unleashing the Full Potential of Product Quantization for Large-Scale Image Retrieval

Yu Liang · Shiliang Zhang · Li Ken Li · Xiaoyu Wang

Training Your Image Restoration Network Better with Random Weight Network as Optimization Function

man zhou · Naishan Zheng · Yuan Xu · Chun-Le Guo · Chongyi Li

RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation

MD WAHIDUZZAMAN KHAN · Hongwei Sheng · Hu Zhang · Heming Du · Sen Wang · Minas Coroneo · Farshid Hajati · Sahar Shariflou · Michael Kalloniatis · Jack Phu · Ashish Agar · Zi Huang · S.Mojtaba Golzan · Xin Yu

Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs

Peng Jin · Yang Wu · Yanbo Fan · Zhongqian Sun · Wei Yang · Li Yuan

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks

Micah Goldblum · Hossein Souri · Renkun Ni · Manli Shu · Viraj Prabhu · Gowthami Somepalli · Prithvijit Chattopadhyay · Mark Ibrahim · Adrien Bardes · Judy Hoffman · Rama Chellappa · Andrew Wilson · Tom Goldstein

RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments

Mengxue Qu · Yu Wu · Wu Liu · Xiaodan Liang · Jingkuan Song · Yao Zhao · Yunchao Wei

On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes

Rajat Modi · Vibhav Vineet · Yogesh Rawat

TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning

Shuo Sun · Molei Qin · Wentao Zhang · Haochong Xia · Chuqiao Zong · Jie Ying · Yonggang Xie · Lingxuan Zhao · Xinrun Wang · Bo An

How to Data in Datathons

Carlos Mougan · Richard Plant · Clare Teng · Marya Bazzi · Alvaro Cabrejas Egea · Ryan Chan · David Salvador Jasin · Martin Stoffel · Kirstie Whitaker · JULES MANSER

Parallel-mentoring for Offline Model-based Optimization

Can (Sam) Chen · Christopher Beckham · Zixuan Liu · Xue (Steve) Liu · Chris Pal

OpenProteinSet: Training data for structural biology at scale

Gustaf Ahdritz · Nazim Bouatta · Sachin Kadyan · Lukas Jarosch · Dan Berenberg · Ian Fisk · Andrew Watkins · Stephen Ra · Richard Bonneau · Mohammed AlQuraishi

RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing

Antoine Scardigli · Lukas Cavigelli · Lorenz K. Müller

AndroidInTheWild: A Large-Scale Dataset For Android Device Control

Christopher Rawles · Alice Li · Daniel Rodriguez · Oriana Riva · Timothy Lillicrap

Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning

Fuqi Jia · Yuhang Dong · Minghao Liu · Pei Huang · Feifei Ma · Jian Zhang

Realistic Synthetic Financial Transactions for Anti-Money Laundering Models

Erik Altman · Jovan Blanuša · Luc von Niederhäusern · Beni Egressy · Andreea Anghel · Kubilay Atasu

Lending Interaction Wings to Recommender Systems with Conversational Agents

Jiarui Jin · Xianyu Chen · Fanghua Ye · Mengyue Yang · Yue Feng · Weinan Zhang · Yong Yu · Jun Wang

Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations

Jungtaek Kim · Mingxuan Li · Oliver Hinder · Paul Leu

Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio

Xudong XU · Dejan Markovic · Jacob Sandakly · Todd Keebler · Steven Krenn · Alexander Richard

Pairwise GUI Dataset Construction Between Android Phones and Tablets

han hu · Haolan Zhan · Yujin Huang · Di Liu

Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction

Ruoyu Li · Qing Li · Yu Zhang · Dan Zhao · Yong Jiang · Yong Yang

DISCO-10M: A Large-Scale Music Dataset

Luca Lanzendörfer · Florian Grötschla · Emil Funke · Roger Wattenhofer

MVDoppler: Unleashing the Power of Multi-View Doppler for MicroMotion-based Gait Classification

Soheil Hor · Shubo Yang · Jaeho Choi · Amin Arbabian

DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model

Yuanshao Zhu · Yongchao Ye · Shiyao Zhang · Xiangyu Zhao · James Yu

Hyper-Skin: A Hyperspectral Dataset for Reconstructing Facial Skin-Spectra from RGB Images

Pai Chet Ng · Zhixiang Chi · Yannick Verdie · Juwei Lu · Konstantinos N Plataniotis

Deep Momentum Multi-Marginal Schrödinger Bridge

Tianrong Chen · Guan-Horng Liu · Molei Tao · Evangelos Theodorou

CHAMMI: A benchmark for channel-adaptive models in microscopy imaging

Zitong Sam Chen · Chau Pham · Siqi Wang · Michael Doron · Nikita Moshkov · Bryan Plummer · Juan C. Caicedo

Into the Single Cell Multiverse: an End-to-End Dataset for Procedural Knowledge Extraction in Biomedical Texts

Ruth Dannenfelser · Jeffrey Zhong · Ran Zhang · Vicky Yao

ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics

Zhangyang Gao · Cheng Tan · Yijie Zhang · Xingran Chen · Lirong Wu · Stan Z. Li

NIS3D: A Completely Annotated Benchmark for Dense 3D Nuclei Image Segmentation

Wei Zheng · Cheng Peng · Zeyuan Hou · Boyu Lyu · Mengfan Wang · Xuelong Mi · Shuoxuan Qiao · Yinan Wan · Guoqiang Yu

SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark

Zeyu Zhang · Robert Pless · Nadia Shakoor · Austin Carnahan · Abby Stylianou

CSMeD: Bridging the Dataset Gap in Automated Citation Screening for Systematic Literature Reviews

Wojciech Kusa · Oscar E. Mendoza · Matthias Samwald · Petr Knoth · Allan Hanbury

PPi: Pretraining Brain Signal Model for Patient-independent Seizure Detection

Zhizhang Yuan · Daoze Zhang · YANG YANG · Junru Chen · Yafeng Li

SARAMIS: Simulation Assets for Robotic Assisted and Minimally Invasive Surgery

Nina Montana-Brown · Shaheer U. Saeed · Ahmed Abdulaal · Thomas Dowrick · Yakup Kilic · Sophie Wilkinson · Jack Gao · Meghavi Mashar · Chloe He · Alkisti Stavropoulou · Emma Thomson · Zachary MC Baum · Simone Foti · Brian Davidson · Yipeng Hu · Matthew Clarkson

Intelligent Knee Sleeves: A Real-time Multimodal Dataset for 3D Lower Body Motion Estimation Using Smart Textile

Wenwen Zhang · Arvin Tashakori · Zenan Jiang · Amir Servati · Harishkumar Narayana · Saeid Soltanian · Rou Yi Yeap · Menghan Ma · Lauren Toy · Peyman Servati

MedSat: A Public Health Dataset for England Featuring Medical Prescriptions and Satellite Imagery

Sanja Scepanovic · Ivica Obadic · Sagar Joglekar · Laura GIUSTARINI · Cristiano Nattero · Daniele Quercia · Xiaoxiang Zhu

Benchmarking Encoder-Decoder Architectures for Biplanar X-ray to 3D Bone Shape Reconstruction

Mahesh Shakya · Bishesh Khanal

YouTubePD: A Multimodal Benchmark for Parkinson’s Disease Analysis

Andy Zhou · Samuel Li · Pranav Sriram · Xiang Li · Jiahua Dong · Ansh Sharma · Yuanyi Zhong · Shirui Luo · Volodymyr Kindratenko · George Heintz · Christopher Zallek · Yu-Xiong Wang

Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization

Hongzheng Yang · Cheng Chen · Yueyao CHEN · Scheppach · Hon Chi Yip · DOU QI

Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions

Çağlar Hızlı · ST John · Anne Juuti · Tuure Saarinen · Kirsi Pietiläinen · Pekka Marttinen

EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models

Michael Wornow · Rahul Thapa · Ethan Steinberg · Jason Fries · Nigam Shah

Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine

Emma Chen · Aman Kansal · Julie Chen · Boyang Tom Jin · Julia Reisler · David Kim · Pranav Rajpurkar

LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

Chunyuan Li · Cliff Wong · Sheng Zhang · Naoto Usuyama · Haotian Liu · Jianwei Yang · Tristan Naumann · Hoifung Poon · Jianfeng Gao

INSPECT: A Multimodal Dataset for Patient Outcome Prediction of Pulmonary Embolisms

Shih-Cheng Huang · Zepeng Huo · Ethan Steinberg · Chia-Chun Chiang · Curtis Langlotz · Matthew Lungren · Serena Yeung · Nigam Shah · Jason Fries

ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram

Jungwoo Oh · Gyubok Lee · Seongsu Bae · Joon-myoung Kwon · Edward Choi

Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses

Elena Sizikova · Niloufar Saharkhiz · Diksha Sharma · Miguel Lago · Berkman Sahiner · Jana Delfino · Aldo Badano

LoRA: A Logical Reasoning Augmented Dataset for Visual Question Answering

Jingying Gao · Qi Wu · Alan Blair · Maurice Pagnucco

Self-Refine: Iterative Refinement with Self-Feedback

Aman Madaan · Niket Tandon · Prakhar Gupta · Skyler Hallinan · Luyu Gao · Sarah Wiegreffe · Uri Alon · Nouha Dziri · Shrimai Prabhumoye · Yiming Yang · Shashank Gupta · Bodhisattwa Prasad Majumder · Katherine Hermann · Sean Welleck · Sean Welleck · Amir Yazdanbakhsh · Peter Clark

QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data

Simone Papicchio · Paolo Papotti · Luca Cagliero

Alexa Arena: A User-Centric Interactive Platform for Embodied AI

Qiaozi Gao · Govind Thattai · Suhaila Shakiah · Xiaofeng Gao · Shreyas Pansare · Vasu Sharma · Gaurav Sukhatme · Hangjie Shi · Bofei Yang · Desheng Zhang · Lucy Hu · Karthika Arumugam · Shui Hu · Matthew Wen · Dinakar Guthy · Shunan Chung · Rohan Khanna · Osman Ipek · Leslie Ball · Kate Bland · Heather Rocker · Michael Johnston · Reza Ghanadan · Dilek Hakkani-Tur · Prem Natarajan

CMMA: Benchmarking Multi-Affection Detection in Chinese Multi-Modal Conversations

Yazhou Zhang · Yang Yu · Qing Guo · Benyou Wang · Dongming Zhao · Sagar Uprety · Dawei Song · Qiuchi Li · Jing Qin

Mind2Web: Towards a Generalist Agent for the Web

Xiang Deng · Yu Gu · Boyuan Zheng · Shijie Chen · Sam Stevens · Boshi Wang · Huan Sun · Yu Su

HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face

Yongliang Shen · Kaitao Song · Xu Tan · Dongsheng Li · Weiming Lu · Yueting Zhuang

Text Alignment Is An Efficient Unified Model for Massive NLP Tasks

Yuheng Zha · Yichi Yang · Ruichen Li · Zhiting Hu

Reflexion: language agents with verbal reinforcement learning

Noah Shinn · Federico Cassano · Ashwin Gopinath · Karthik Narasimhan · Shunyu Yao

DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation Learning

Alexander Liu · Heng-Jui Chang · Michael Auli · Wei-Ning Hsu · Jim Glass

BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing

Subhro Roy · Samuel Thomson · Tongfei Chen · Richard Shin · Adam Pauls · Jason Eisner · Benjamin Van Durme

Beyond MLE: Convex Learning for Text Generation

Chenze Shao · Zhengrui Ma · Min Zhang · Yang Feng

Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks

Minki Kang · Seanie Lee · Jinheon Baek · Kenji Kawaguchi · Sung Ju Hwang

Benchmarking Foundation Models with Language-Model-as-an-Examiner

Yushi Bai · Jiahao Ying · Yixin Cao · Xin Lv · Yuze He · Xiaozhi Wang · Jifan Yu · Kaisheng Zeng · Yijia Xiao · Haozhe Lyu · Jiayin Zhang · Juanzi Li · Lei Hou

A Massive Scale Semantic Similarity Dataset of Historical English

Emily Silcock · Abhishek Arora · Melissa Dell

FACE: Evaluating Natural Language Generation with Fourier Analysis of Cross-Entropy

Zuhao Yang · Yingfang Yuan · Yang Xu · SHUO ZHAN · Huajun Bai · Kefan Chen

Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs

Jinyang Li · Binyuan Hui · Ge Qu · Jiaxi Yang · Binhua Li · Bowen Li · Bailin Wang · Bowen Qin · Ruiying Geng · Nan Huo · Xuanhe Zhou · Ma Chenhao · Guoliang Li · Kevin Chang · Fei Huang · Reynold Cheng · Yongbin Li

M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models

Wenxuan Zhang · Mahani Aljunied · Chang Gao · Yew Ken Chia · Lidong Bing

CARE-MI: Chinese Benchmark for Misinformation Evaluation in Maternity and Infant Care

Tong Xiang · Liangzhi Li · Wangyue Li · Mingbai Bai · Lu Wei · Bowen Wang · Noa Garcia

InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback

John Yang · Akshara Prabhakar · Karthik Narasimhan · Shunyu Yao

YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus

Dave Uthus · Garrett Tanzer · Manfred Georg

MultiVENT: Multilingual Videos of Events and Aligned Natural Text

Kate Sanders · David Etter · Reno Kriz · Benjamin Van Durme

FELM: Benchmarking Factuality Evaluation of Large Language Models

shiqi chen · Yiran Zhao · Jinghan Zhang · I-Chun Chern · Siyang Gao · Pengfei Liu · Junxian He

Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning

Beichen Zhang · Kun Zhou · Xilin Wei · Xin Zhao · Jing Sha · Shijin Wang · Ji-Rong Wen

American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers

Melissa Dell · Jacob Carlson · Tom Bryan · Emily Silcock · Abhishek Arora · Zejiang Shen · Luca D'Amico-Wong · Quan Le · Pablo Querubin · Leander Heldring

PTADisc: A Cross-Course Dataset Supporting Personalized Learning in Cold-Start Scenarios

Liya Hu · Zhiang Dong · Jingyuan Chen · Guifeng Wang · Zhihua Wang · Zhou Zhao · Fei Wu

The ToMCAT Dataset

Adarsh Pyarelal · Eric Duong · Caleb Shibu · Paulo Soares · Savannah Boyd · Payal Khosla · Valeria A. Pfeifer · Diheng Zhang · Eric Andrews · Rick Champlin · Vincent Raymond · Meghavarshini Krishnaswamy · Clayton Morrison · Emily Butler · Kobus Barnard

The Simplicity Bias in Multi-Task RNNs: Shared Attractors, Reuse of Dynamics, and Geometric Representation

Elia Turner · Omri Barak

Decoding the Enigma: Benchmarking Humans and AIs on the Many Facets of Working Memory

Ankur Sikarwar · Mengmi Zhang

A Bounded Ability Estimation for Computerized Adaptive Testing

Yan Zhuang · Qi Liu · Guanhao Zhao · Zhenya Huang · Weizhe Huang · Zachary Pardos · Enhong Chen · Jinze Wu · Xin Li

Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties

Hsiao-Yu Tung · Mingyu Ding · Zhenfang Chen · Daniel Bear · Chuang Gan · Josh Tenenbaum · Dan Yamins · Judith Fan · Kevin Smith

SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction

Kushin Mukherjee · Holly Huey · Xuanchen Lu · Yael Vinker · Rio Aguina-Kang · Ariel Shamir · Judith Fan

Transformer as a hippocampal memory consolidation model based on NMDAR-inspired nonlinearity

Dong Kyum Kim · Jea Kwon · Meeyoung Cha · C. Lee

Hyper-HMM: aligning human brains and semantic features in a common latent event space

Caroline Lee · Jane Han · Ma Feilong · Guo Jiahui · James Haxby · Christopher Baldassano

Interactive Visual Reasoning under Uncertainty

Manjie Xu · Guangyuan Jiang · Wei Liang · Chi Zhang · Yixin Zhu

Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes

Yizi Zhang · Tianxiao He · Julien Boussard · Charles Windolf · Olivier Winter · Eric Trautmann · Noam Roth · Hailey Barrell · Mark Churchland · Nicholas A Steinmetz · Erdem Varol · Cole Hurwitz · Liam Paninski

Understanding Social Reasoning in Language Models with Language Models

Kanishk Gandhi · Jan-Philipp Fraenken · Tobias Gerstenberg · Noah Goodman

Curriculum Learning With Infant Egocentric Videos

Saber Sheybani · Himanshu Hansaria · Justin Wood · Linda Smith · Zoran Tiganj

Adaptive whitening with fast gain modulation and slow synaptic plasticity

Lyndon Duong · Eero Simoncelli · Dmitri Chklovskii · David Lipshutz

A Unified, Scalable Framework for Neural Population Decoding

Mehdi Azabou · Vinam Arora · Venkataramana Ganesh · Ximeng Mao · Santosh Nachimuthu · Michael Mendelson · Blake Richards · Matthew Perich · Guillaume Lajoie · Eva Dyer

Enhancing Knowledge Transfer for Task Incremental Learning with Data-free Subnetwork

Qiang Gao · Xiaojun Shan · Yuchen Zhang · Fan Zhou

A generative model of the hippocampal formation trained with theta driven local learning rules

Tom M George · Kimberly Stachenfeld · Caswell Barry · Claudia Clopath · Tomoki Fukai

Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs

Dominik Straub · Matthias Schultheis · Heinz Koeppl · Constantin Rothkopf

SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks

Rainer Engelken

LithoBench: Benchmarking AI Computational Lithography for Semiconductor Manufacturing

Su Zheng · Haoyu Yang · Binwu Zhu · Bei Yu · Martin Wong

LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite

Artur Toshev · Gianluca Galletti · Fabian Fritz · Stefan Adami · Nikolaus Adams

Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations

Anudhyan Boral · Zhong Yi Wan · Leonardo Zepeda-Núñez · James Lottes · Qing Wang · Yi-Fan Chen · John Anderson · Fei Sha

M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery

Yuanqi Du · Yingheng Wang · Yining Huang · Jianan Canal Li · Yanqiao Zhu · Tian Xie · Chenru Duan · John Gregoire · Carla Gomes

RoboHive: A Unified Framework for Robot Learning

Vikash Kumar · Rutav Shah · Gaoyue Zhou · Vincent Moens · Vittorio Caggiano · Abhishek Gupta · Aravind Rajeswaran

Safety Gymnasium: A Unified Safe Reinforcement Learning Benchmark

Jiaming Ji · Borong Zhang · Jiayi Zhou · Xuehai Pan · Weidong Huang · Ruiyang Sun · Yiran Geng · Yifan Zhong · Josef Dai · Yaodong Yang

The Waymo Open Sim Agents Challenge

Nico Montali · John Lambert · Paul Mougin · Alex Kuefler · Nicholas Rhinehart · Michelle Li · Cole Gulino · Tristan Emrich · Zoey Yang · Shimon Whiteson · Brandyn White · Dragomir Anguelov

HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count

Noah Wiederhold · Ava Megyeri · DiMaggio Paris · Sean Banerjee · Natasha Banerjee

CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes

Xiaohan Wang · Yuehu Liu · Xinhang Song · Beibei Wang · Shuqiang Jiang

SiT Dataset: Socially Interactive Pedestrian Trajectory Dataset for Social Navigation Robots

Jong Wook Bae · Jungho Kim · Junyong Yun · Changwon Kang · Jeongseon Choi · Chanhyeok Kim · Junho Lee · Jungwook Choi · Jun Won Choi

BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting

Patrick Emami · Abhijeet Sahu · Peter Graf

WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting

Yuxin Jia · Youfang Lin · Xinyan Hao · Yan Lin · Shengnan Guo · Huaiyu Wan

BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis

Zelin Ni · Hang Yu · Shizhan Liu · Jianguo Li · Weiyao Lin

A Dataset for Analyzing Streaming Media Performance over HTTP/3 Browsers

Sapna Chaudhary · Mukulika Maity · Sandip Chakraborty · Naval Shukla

CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement

Qihe Huang · Lei Shen · Ruixin Zhang · Shouhong Ding · Binwu Wang · Zhengyang Zhou · Yang Wang

Data Pruning via Moving-one-Sample-out

Haoru Tan · Sitong Wu · Fei Du · Yukang Chen · Zhibin Wang · Fan Wang · Xiaojuan Qi

Scientific Document Retrieval using Multi-level Aspect-based Queries

Jianyou (Andre) Wang · Kaicheng Wang · Xiaoyue Wang · Prudhviraj Naidu · Leon Bergen · Ramamohan Paturi

Data Portraits: Recording Foundation Model Training Data

Marc Marone · Benjamin Van Durme

Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias

Yue Yu · Yuchen Zhuang · Jieyu Zhang · Yu Meng · Alexander Ratner · Ranjay Krishna · Jiaming Shen · Chao Zhang

SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality

Cheng-Yu Hsieh · Jieyu Zhang · Zixian Ma · Aniruddha Kembhavi · Ranjay Krishna

D4: Improving LLM Pretraining via Document De-Duplication and Diversification

Kushal Tirumala · Daniel Simig · Armen Aghajanyan · Ari Morcos

Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs

Yunsheng Bai · Atefeh Sohrabizadeh · Zongyue Qin · Ziniu Hu · Yizhou Sun · Jason Cong

Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmark

Lukasz Augustyniak · Szymon Woźniak · Marcin Gruza · Piotr Gramacki · Krzysztof Rajda · Mikołaj Morzy · Tomasz Kajdanowicz

Residual Alignment: Uncovering the Mechanisms of Residual Networks

Jianing Li · Vardan Papyan

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Rafael Rafailov · Archit Sharma · Eric Mitchell · Christopher D Manning · Stefano Ermon · Chelsea Finn

Lung250M-4B: A Combined 3D Dataset for CT- and Point Cloud-Based Intra-Patient Lung Registration

Fenja Falta · Christoph Großbröhmer · Alessa Hering · Alexander Bigalke · Mattias Heinrich

The Tunnel Effect: Building Data Representations in Deep Neural Networks

Wojciech Masarczyk · Mateusz Ostaszewski · Ehsan Imani · Razvan Pascanu · Piotr Miłoś · Tomasz Trzcinski

Algorithm Selection for Deep Active Learning with Imbalanced Datasets

Jifan Zhang · Shuai Shao · Saurabh Verma · Robert Nowak

Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity

Zhanpeng Zhou · Yongyi Yang · Xiaojiang Yang · Junchi Yan · Wei Hu

ADGym: Design Choices for Deep Anomaly Detection

Minqi Jiang · Chaochuan Hou · Ao Zheng · Songqiao Han · Hailiang Huang · Qingsong Wen · Xiyang Hu · Yue Zhao

Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization

Yan Sun · Li Shen · Dacheng Tao

Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context

Oussama Boussif · Ghait Boukachab · Dan Assouline · Stefano Massaroli · Tianle Yuan · Loubna Benabbou · Yoshua Bengio

Grounding Neural Inference with Satisfiability Modulo Theories

Zifan Wang · Saranya Vijayakumar · Kaiji Lu · Vijay Ganesh · Somesh Jha · Matt Fredrikson

A Comprehensive Benchmark for Neural Human Radiance Fields

Kenkun Liu · Derong Jin · Ailing Zeng · Xiaoguang Han · Lei Zhang

Sampling weights of deep neural networks

Erik L Bolager · Iryna Burak · Chinmay Datar · Qing Sun · Felix Dietrich

VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset

Sihan Chen · Handong Li · Qunbo Wang · Zijia Zhao · Mingzhen Sun · Xinxin Zhu · Jing Liu

No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models

Jean Kaddour · Oscar Key · Piotr Nawrot · Pasquale Minervini · Matt Kusner

Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers

Sotiris Anagnostidis · Dario Pavllo · Luca Biggio · Lorenzo Noci · Aurelien Lucchi · Thomas Hofmann

$S^3$: Increasing GPU Utilization during Generative Inference for Higher Throughput

Yunho Jin · Chun-Feng Wu · David Brooks · Gu-Yeon Wei

Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers

Zixuan Jiang · Jiaqi Gu · Hanqing Zhu · David Pan

Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing

Yelysei Bondarenko · Markus Nagel · Tijmen Blankevoort

XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information

Zitao Liu · Qiongqiong Liu · Teng Guo · Jiahao Chen · Shuyan Huang · Xiangyu Zhao · Jiliang Tang · Weiqi Luo · Jian Weng

Stable and low-precision training for large-scale vision-language models

Mitchell Wortsman · Tim Dettmers · Luke Zettlemoyer · Ari Morcos · Ali Farhadi · Ludwig Schmidt

Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels

Jian Chen · Ruiyi Zhang · Tong Yu · Rohan Sharma · Zhiqiang Xu · Tong Sun · Changyou Chen

Stable Diffusion is Unstable

Chengbin Du · Yanxi Li · Zhongwei Qiu · Chang Xu

InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Wenliang Dai · Junnan Li · Junnan Li · DONGXU LI · Anthony Tiong · Anthony Meng Huat Tiong · Junqi Zhao · Weisheng Wang · Boyang Li · Pascale N Fung · Steven Hoi

Compositional Sculpting of Iterative Generative Processes

Timur Garipov · Sebastiaan De Peuter · Ge Yang · Vikas Garg · Samuel Kaski · Tommi Jaakkola

Cocktail: Mixing Multi-Modality Control for Text-Conditional Image Generation

Minghui Hu · Jianbin Zheng · Daqing Liu · Chuanxia Zheng · Chaoyue Wang · Dacheng Tao · Tat-Jen Cham

Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability

Maciej Falkiewicz · Naoya Takeishi · Imahn Shekhzadeh · Antoine Wehenkel · Arnaud Delaunoy · Gilles Louppe · Alexandros Kalousis

Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning

Yingcong Li · Kartik Sreenivasan · Angeliki Giannou · Dimitris Papailiopoulos · Samet Oymak

Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark

Lasse Hansen · Nabeel Seedat · Mihaela van der Schaar · Andrija Petrovic

Dynamically Masked Discriminator for GANs

Wentian Zhang · Haozhe Liu · Bing Li · Jinheng Xie · Yawen Huang · Yuexiang Li · Yefeng Zheng · Bernard Ghanem

A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems

Matthew Bendel · Rizwan Ahmad · Philip Schniter

Revisiting the Evaluation of Image Synthesis with GANs

mengping yang · Ceyuan Yang · Yichi Zhang · Qingyan Bai · Yujun Shen · Bo Dai

Benchmarking Large Language Models on CMExam - A comprehensive Chinese Medical Exam Dataset

Junling Liu · Peilin Zhou · Yining Hua · Dading Chong · Zhongyu Tian · Andrew Liu · Helin Wang · Chenyu You · Zhenhua Guo · LEI ZHU · Michael Lingzhi Li

Benchmarking and Analyzing 3D-aware Image Synthesis with a Modularized Codebase

Qiuyu Wang · Zifan Shi · Kecheng Zheng · Yinghao Xu · Sida Peng · Yujun Shen

CAPP-130: A Corpus of Chinese Application Privacy Policy Summarization and Interpretation

pengyun zhu · Long Wen · Jinfei Liu · Feng Xue · Jian Lou · Zhibo Wang · Kui Ren

UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild

Can Qin · Shu Zhang · Ning Yu · Yihao Feng · Xinyi Yang · Yingbo Zhou · Huan Wang · Juan Carlos Niebles · Caiming Xiong · Silvio Savarese · Stefano Ermon · Yun Fu · Ran Xu

One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models

Ba-Hien Tran · Giulio Franzese · Pietro Michiardi · Maurizio Filippone

GenEval: An object-focused framework for evaluating text-to-image alignment

Dhruba Ghosh · Hannaneh Hajishirzi · Ludwig Schmidt

Star-Shaped Denoising Diffusion Probabilistic Models

Andrey Okhotin · Dmitry Molchanov · Arkhipkin Vladimir · Grigory Bartosh · Viktor Ohanesian · Aibek Alanov · Dmitry Vetrov

Trans-Dimensional Generative Modeling via Jump Diffusion Models

Andrew Campbell · William Harvey · Christian Weilbach · Valentin De Bortoli · Thomas Rainforth · Arnaud Doucet

Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark

Nikita Gushchin · Alexander Kolesov · Petr Mokrov · Polina Karpikova · Andrei Spiridonov · Evgeny Burnaev · Alexander Korotin

High-dimensional Asymptotics of Denoising Autoencoders

Hugo Cui · Lenka Zdeborová

The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data Only

Guilherme Penedo · Quentin Malartic · Daniel Hesslow · Ruxandra Cojocaru · Hamza Alobeidli · Alessandro Cappelli · Baptiste Pannier · Ebtesam Almazrouei · Julien Launay

SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds

Yanyu Li · Huan Wang · Qing Jin · Ju Hu · Pavlo Chemerys · Yun Fu · Yanzhi Wang · Sergey Tulyakov · Jian Ren

Extremal Domain Translation with Neural Optimal Transport

Milena Gazdieva · Alexander Korotin · Daniil Selikhanovych · Evgeny Burnaev

Canonical normalizing flows for manifold learning

Kyriakos Flouris · Ender Konukoglu

Restart Sampling for Improving Generative Processes

Yilun Xu · Mingyang Deng · Xiang Cheng · Yonglong Tian · Ziming Liu · Tommi Jaakkola

OpenAGI: When LLM Meets Domain Experts

Yingqiang Ge · Wenyue Hua · Kai Mei · jianchao ji · Juntao Tan · Shuyuan Xu · Zelong Li · Yongfeng Zhang

Leveraging Early-Stage Robustness in Diffusion Models for Efficient and High-Quality Image Synthesis

Yulhwa Kim · Dongwon Jo · Hyesung Jeon · Taesu Kim · Daehyun Ahn · Hyungjun Kim · jae-joon kim

Optimality of Message-Passing Architectures for Sparse Graphs

Aseem Baranwal · Kimon Fountoulakis · Aukosh Jagannath

Graph Neural Networks for Road Safety Modeling: Datasets and Evaluations for Accident Analysis

Abhinav Nippani · Dongyue Li · Haotian Ju · Haris Koutsopoulos · Hongyang Zhang

Expressivity-Preserving GNN Simulation

Fabian Jogl · Maximilian Thiessen · Thomas Gärtner

Latent Graph Inference with Limited Supervision

Jianglin Lu · Yi Xu · Huan Wang · Yue Bai · Yun Fu

Improving Self-supervised Molecular Representation Learning using Persistent Homology

Yuankai Luo · Lei Shi · Veronika Thost

A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks

Vignesh Kothapalli · Tom Tirer · Joan Bruna

FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations

Chanakya Ekbote · Ajinkya Deshpande · Arun Iyer · SUNDARARAJAN SELLAMANICKAM · Ramakrishna Bairi

On Class Distributions Induced by Nearest Neighbor Graphs for Node Classification of Tabular Data

Federico Errica

Tailoring Self-Attention for Graph via Rooted Subtrees

Siyuan Huang · Yunchong Song · Jiayue Zhou · Zhouhan Lin

Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking

Juanhui Li · Harry Shomer · Haitao Mao · Shenglai Zeng · Yao Ma · Neil Shah · Jiliang Tang · Dawei Yin

Uncertainty Quantification over Graph with Conformalized Graph Neural Networks

Kexin Huang · Ying Jin · Emmanuel Candes · Jure Leskovec

Fused Gromov-Wasserstein Graph Mixup for Graph-level Classifications

Xinyu Ma · Xu Chu · Yasha Wang · Yang Lin · Junfeng Zhao · Liantao Ma · Wenwu Zhu

The expressive power of pooling in Graph Neural Networks

Filippo Maria Bianchi · Veronica Lachi

Towards Better Dynamic Graph Learning: New Architecture and Unified Library

Le Yu · Leilei Sun · Bowen Du · Weifeng Lv

Graph Clustering with Graph Neural Networks

Anton Tsitsulin · John Palowitch · Bryan Perozzi · Emmanuel Müller

GLEMOS: Benchmark for Instantaneous Graph Learning Model Selection

Namyong Park · Ryan Rossi · Xing Wang · Antoine Simoulin · Nesreen K. Ahmed · Christos Faloutsos

Neural Algorithmic Reasoning Without Intermediate Supervision

Gleb Rodionov · Liudmila Prokhorenkova

NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics

Anwar Said · Roza Bayrak · Tyler Derr · Mudassir Shabbir · Daniel Moyer · Catie Chang · Xenofon Koutsoukos

GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection

Jianheng Tang · Fengrui Hua · Ziqi Gao · Peilin Zhao · Jia Li

PlanE: Representation Learning over Planar Graphs

Radoslav Dimitrov · Zeyang Zhao · Ralph Abboud · Ismail Ceylan

Human-Guided Complexity-Controlled Abstractions

Andi Peng · Mycal Tucker · Eoin Kenny · Noga Zaslavsky · Pulkit Agrawal · Julie A Shah

Balanced Training for Sparse GANs

Yite Wang · Jing Wu · NAIRA HOVAKIMYAN · Ruoyu Sun

ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets

Damien Teney · Yong Lin · Seong Joon Oh · Ehsan Abbasnejad

Revealing the unseen: Benchmarking video action recognition under occlusion

Shresth Grover · Vibhav Vineet · Yogesh Rawat

How hard are computer vision datasets? Calibrating dataset difficulty to viewing time

David Mayo · Jesse Cummings · Xinyu Lin · Dan Gutfreund · Boris Katz · Andrei Barbu

On Evaluating Adversarial Robustness of Large Vision-Language Models

Yunqing Zhao · Tianyu Pang · Chao Du · Xiao Yang · Chongxuan LI · Ngai-Man (Man) Cheung · Min Lin

QuadAttac$K$: A Quadratic Programming Approach to Learning Ordered Top-$K$ Adversarial Attacks

Thomas Paniagua · Ryan Grainger · Tianfu Wu

Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift

Saurabh Garg · Amrith Setlur · Zachary Lipton · Sivaraman Balakrishnan · Virginia Smith · Aditi Raghunathan

Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data

Boris van Breugel · Nabeel Seedat · Fergus Imrie · Mihaela van der Schaar

COCO-Counterfactuals: Automatically Constructed Counterfactual Examples for Image-Text Pairs

Tiep Le · VASUDEV LAL · Phillip Howard

Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models

Shuo Chen · Jindong Gu · Zhen Han · Yunpu Ma · Philip Torr · Volker Tresp

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning

Florian Bordes · Shashank Shekhar · Mark Ibrahim · Diane Bouchacourt · Pascal Vincent · Ari Morcos

Benchmarking Distribution Shift in Tabular Data with TableShift

Josh Gardner · Zoran Popovic · Ludwig Schmidt

Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach

Kai Zhao · Qiyu Kang · Yang Song · Rui She · Sijie Wang · Wee Peng Tay

Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness

Xinli Yue · Mou Ningping · Qian Wang · Lingchen Zhao

Benchmarking Robustness to Adversarial Image Obfuscations

Florian Stimberg · Ayan Chakrabarti · Chun-Ta Lu · Hussein Hazimeh · Otilia Stretcu · Wei Qiao · Yintao Liu · Merve Kaya · Cyrus Rashtchian · Ariel Fuxman · Mehmet Tek · Sven Gowal

Exploring Geometry of Blind Spots in Vision models

Sriram Balasubramanian · Gaurang Sriramanan · Vinu Sankar Sadasivan · Soheil Feizi

Maximization of Average Precision for Deep Learning with Adversarial Ranking Robustness

Gang Li · Gang Li · Wei Tong · Tianbao Yang

Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration

Jie Xu · Shuo Chen · Yazhou Ren · Xiaoshuang Shi · Hengtao Shen · Gang Niu · Xiaofeng Zhu

Contextually Affinitive Neighborhood Refinery for Deep Clustering

Chunlin Yu · Ye Shi · Jingya Wang

HASSOD: Hierarchical Adaptive Self-Supervised Object Detection

Shengcao Cao · Dhiraj Joshi · Liangyan Gui · Yu-Xiong Wang

Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities

Andrii Zadaianchuk · Maximilian Seitzer · Georg Martius

Self-supervised video pretraining yields robust and more human-aligned visual representations

Nikhil Parthasarathy · S. M. Ali Eslami · Joao Carreira · Olivier Henaff

LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

Duy M. H. Nguyen · Hoang Nguyen · Nghiem Diep · Tan Ngoc Pham · Tri Cao · Binh Nguyen · Paul Swoboda · Paul Swoboda · Nhat Ho · Shadi Albarqouni · Pengtao Xie · Pengtao Xie · Daniel Sonntag · Mathias Niepert

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners

Yonglong Tian · Lijie Fan · Phillip Isola · Huiwen Chang · Dilip Krishnan

Siamese Masked Autoencoders

Agrim Gupta · Jiajun Wu · Jia Deng · Fei-Fei Li

Implicit variance regularization in non-contrastive SSL

Manu Srinath Halvagal · Axel Laborieux · Friedemann Zenke

A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective

Chenhang Cui · Yazhou Ren · Jingyu Pu · Jiawei Li · Xiaorong Pu · Tianyi Wu · Yutao Shi · Lifang He

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

Cheng Tan · Siyuan Li · Zhangyang Gao · Wenfei Guan · Zedong Wang · Zicheng Liu · Lirong Wu · Stan Z. Li

ForecastPFN: Synthetically-Trained Zero-Shot Forecasting

Samuel Dooley · Gurnoor Singh Khurana · Chirag Mohapatra · Siddartha V Naidu · Colin White

Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency

Owen Queen · Tom Hartvigsen · Teddy Koker · Huan He · Theodoros Tsiligkaridis · Marinka Zitnik

Deep Equilibrium Based Neural Operators for Steady-State PDEs

Tanya Marwah · Ashwini Pokle · J. Zico Kolter · Zachary Lipton · Jianfeng Lu · Andrej Risteski

What can a Single Attention Layer Learn? A Study Through the Random Features Lens

Hengyu Fu · Tianyu Guo · Yu Bai · Song Mei

Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model

Peter Súkeník · Marco Mondelli · Christoph Lampert

Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles

Ben Ruben · Cengiz Pehlevan

PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization

Jiancong Xiao · Ruoyu Sun · Zhi-Quan Luo

Optimal approximation using complex-valued neural networks

Paul Geuchen · Felix Voigtlaender

Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond

Taiji Suzuki · Denny Wu · Kazusato Oko · Atsushi Nitanda

A Logic for Expressing Log-Precision Transformers

William Merrill · Ashish Sabharwal

Learning a 1-layer conditional generative model in total variation

Ajil Jalal · Justin Kang · Ananya Uppal · Kannan Ramchandran · Eric Price

Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs

Dmitry Chistikov · Matthias Englert · Ranko Lazic

Learning Causal Models under Independent Changes

Sarah Mameche · David Kaltenpoth · Jilles Vreeken

Do Not Marginalize Mechanisms, Rather Consolidate!

Moritz Willig · Matej Zečević · Devendra Dhami · Kristian Kersting

BayesDAG: Gradient-Based Posterior Inference for Causal Discovery

Yashas Annadani · Nick Pawlowski · Joel Jennings · Joel Jennings · Stefan Bauer · Cheng Zhang · Wenbo Gong

Unpaired Multi-Domain Causal Representation Learning

Nils Sturma · Chandler Squires · Mathias Drton · Caroline Uhler

Generator Identification for Linear SDEs with Additive and Multiplicative Noise

Yuanyuan Wang · Xi Geng · Wei Huang · Biwei Huang · Mingming Gong

Optimal Treatment Regimes for Proximal Causal Learning

Tao Shen · Yifan Cui

Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling

Zhenyu Zhu · Francesco Locatello · Volkan Cevher

FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation

Jia Gu · Caizhi Tang · Han Yan · Qing Cui · Longfei Li · Jun Zhou

Characterization and Learning of Causal Graphs with Small Conditioning Sets

Murat Kocaoglu

A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models

Alexander Reisach · Myriam Tami · Christof Seiler · Antoine Chambaz · Sebastian Weichwald

Toolbox for Multimodal Learn (scikit-multimodallearn)

Dominique Benielli · Baptiste Bauvin · Sokol Koço · Riikka Huusari · Cécile Capponi · Hachem Kadri · François Laviolette

A benchmark of categorical encoders for binary classification

Federico Matteucci · Vadim Arzamasov · Klemens Böhm

Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework

Weiduo Liao · Ying Wei · Mingchen Jiang · Qingfu Zhang · Hisao Ishibuchi

AQuA: A Benchmarking Tool for Label Quality Assessment

Mononito Goswami · Vedant Sanil · Arjun Choudhry · Arvind Srinivasan · Chalisa Udompanyawit · Artur Dubrawski

Network Regression with Graph Laplacians

Yidong Zhou · Hans-Georg Müller

Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data

Vaidotas Simkus · Benjamin Rhodes · Michael Gutmann

Sharp Calibrated Gaussian Processes

Alexandre Capone · Sandra Hirche · Geoff Pleiss · Geoff Pleiss

MMD Aggregated Two-Sample Test

Antonin Schrab · Ilmun Kim · Mélisande Albert · Béatrice Laurent · Benjamin Guedj · Arthur Gretton

Kernelized Cumulants: Beyond Kernel Mean Embeddings

Patric Bonnier · Harald Oberhauser · Zoltan Szabo

Annotator: A Generic Active Learning Baseline for LiDAR Semantic Segmentation

Binhui Xie · Shuang Li · Qingju Guo · Chi Liu · Xinjing Cheng

Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

Emanuele Marconato · Stefano Teso · Antonio Vergari · Andrea Passerini

Achieving Cross Modal Generalization with Multimodal Unified Representation

Yan Xia · Hai Huang · Jieming Zhu · Zhou Zhao

Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models

Yeongbin Kim · Gautam Singh · Junyeong Park · Caglar Gulcehre · Sungjin Ahn

Fundamental Limits and Tradeoffs in Invariant Representation Learning

Han Zhao · Chen Dan · Bryon Aragam · Tommi Jaakkola · Geoffrey Gordon · Pradeep Ravikumar

Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships

ABHRA CHAUDHURI · Massimiliano Mancini · Zeynep Akata · Zeynep Akata · Anjan Dutta

URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates

Michael Kirchhof · Bálint Mucsányi · Seong Joon Oh · Dr. Enkelejda Kasneci

MARBLE: Music Audio Representation Benchmark for Universal Evaluation

Ruibin Yuan · Yinghao Ma · Yizhi Li · Ge Zhang · Xingran Chen · Hanzhi Yin · zhuo le · Yiqi Liu · Jiawen Huang · Zeyue Tian · Binyue Deng · Ningzhi Wang · Chenghua Lin · Emmanouil Benetos · Anton Ragni · Norbert Gyenge · Roger Dannenberg · Wenhu Chen · Gus Xia · Wei Xue · Si Liu · Shi Wang · Ruibo Liu · Yike Guo · Jie Fu

Uncovering Meanings of Embeddings via Partial Orthogonality

Yibo Jiang · Bryon Aragam · Victor Veitch

Are Emergent Abilities of Large Language Models a Mirage?

Rylan Schaeffer · Brando Miranda · Sanmi Koyejo

An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint

Mengzhao Wang · Lingwei Lv · Xiaoliang Xu · Yuxiang Wang · Qiang Yue · Jiongkang Ni

QuIP: 2-Bit Quantization of Large Language Models With Guarantees

Jerry Chee · Yaohui Cai · Volodymyr Kuleshov · Christopher De Sa

SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning

Yi-Chung Chen · Hsi-Wen Chen · Shun-Gui Wang · Ming-syan Chen

Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask?

Hoang Pham · The Anh Ta · Shiwei Liu · Shiwei Liu · Lichuan Xiang · Dung Le · Hongkai Wen · Long Tran-Thanh

Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics

Gaetano Romano · Idris A. Eckley · Paul Fearnhead · Guillem Rigaill

Augmented Memory Replay-based Continual Learning Approaches for Network Intrusion Detection

suresh kumar amalapuram · Sumohana Channappayya · Bheemarjuna Reddy Tamma

An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions

Michael Scholkemper · Michael T Schaub

Retrieval-Augmented Multiple Instance Learning

Yufei CUI · Ziquan Liu · Yixin Chen · Yuchen Lu · Xinyue Yu · Xue (Steve) Liu · Tei-Wei Kuo · Miguel Rodrigues · Chun Jason Xue · Chun Jason XUE · Antoni Chan

An Empirical Investigation of the Role of Pre-training in Lifelong Learning

Sanket Vaibhav Mehta · Darshan Patil · Sarath Chandar · Emma Strubell

TIES-Merging: Resolving Interference When Merging Models

Prateek Yadav · Derek Tam · Leshem Choshen · Colin Raffel · Mohit Bansal

Practical Equivariances via Relational Conditional Neural Processes

Daolang Huang · Manuel Haussmann · Ulpu Remes · ST John · Grégoire Clarté · Kevin Sebastian Luck · Kevin Luck · Samuel Kaski · Luigi Acerbi

Online Constrained Meta-Learning: Provable Guarantees for Generalization

Siyuan Xu · Minghui Zhu

Focus Your Attention when Few-Shot Classification

Haoqing Wang · Shibo Jie · Zhihong Deng

Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees

Veronica Alvarez · Santiago Mazuelas · Jose A. Lozano

Meta-in-context learning in large language models

Julian Coda-Forno · Marcel Binz · Zeynep Akata · Matt Botvinick · Jane Wang · Eric Schulz

Secure Out-of-Distribution Task Generalization with Energy-Based Models

Shengzhuang Chen · Long-Kai Huang · Jonathan Richard Schwarz · Yilun Du · Ying Wei

Recasting Continual Learning as Sequence Modeling

Soochan Lee · Jaehyeon Son · Gunhee Kim

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models

Guillermo Ortiz-Jimenez · Alessandro Favero · Pascal Frossard

Does progress on ImageNet transfer to real-world datasets?

Alex Fang · Simon Kornblith · Ludwig Schmidt

Data Selection for Language Models via Importance Resampling

Sang Michael Xie · Shibani Santurkar · Tengyu Ma · Percy Liang

Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning

Zixing Song · Yifei Zhang · Irwin King

Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning

Fangchen Yu · Runze Zhao · Zhan Shi · Yiwen Lu · Jicong Fan · Yicheng Zeng · Jianfeng Mao · Wenye Li

InstanT: Semi-supervised Learning with Instance-dependent Thresholds

Muyang Li · Runze Wu · Haoyu Liu · Jun Yu · Xun Yang · Bo Han · Tongliang Liu

Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning

Yu Wang · Yu Wang · Zhun Zhong · Pengchong Qiao · Xuxin Cheng · Xiawu Zheng · Xiawu Zheng · Chang Liu · Nicu Sebe · Rongrong Ji · Jie Chen

Unsupervised Semantic Correspondence Using Stable Diffusion

Eric Hedlin · Gopal Sharma · Shweta Mahajan · Hossam Isack · Abhishek Kar · Andrea Tagliasacchi · Kwang Moo Yi

The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning

Artyom Gadetsky · Maria Brbic

On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective

Zeke Xie · Zhiqiang Xu · Jingzhao Zhang · Issei Sato · Masashi Sugiyama

Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds

Jihun Yun · Eunho Yang

Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start

Riccardo Grazzi · Massimiliano Pontil · Saverio Salzo

Operation-Level Early Stopping for Robustifying Differentiable NAS

Shen Jiang · Zipeng Ji · Guanghui Zhu · Chunfeng Yuan · Yihua Huang

An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition

Quan Xiao · Songtao Lu · Songtao Lu · Tianyi Chen

Complexity of Derivative-Free Policy Optimization for Structured $\mathcal{H}_\infty$ Control

Xingang Guo · Darioush Keivan · Geir Dullerud · Peter Seiler · Bin Hu

Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking

Frederik Kunstner · Victor Sanches Portella · Mark Schmidt · Nicholas Harvey

Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value

Jaeyeon Kim · Asuman Ozdaglar · Chanwoo Park · Ernest Ryu

Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets

Dinghuai Zhang · Hanjun Dai · Nikolay Malkin · Aaron Courville · Yoshua Bengio · Ling Pan

Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case

Taihei Oki · Shinsaku Sakaue

Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization

Ruichen Jiang · Aryan Mokhtari

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Martijn De Vos · Sadegh Farhadkhani · Rachid Guerraoui · Anne-marie Kermarrec · Rafael Pires · Rishi Sharma

Federated Learning with Bilateral Curation for Partially Class-Disjoint Data

Ziqing Fan · ruipeng zhang · Jiangchao Yao · Bo Han · Ya Zhang · Yanfeng Wang

Federated Compositional Deep AUC Maximization

Xinwen Zhang · Yihan Zhang · Tianbao Yang · Richard Souvenir · Hongchang Gao

Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning

Zachary Charles · Nicole Mitchell · Krishna Pillutla · Michael Reneer · Zachary Garrett

Towards Personalized Federated Learning via Heterogeneous Model Reassembly

Jiaqi Wang · Xingyi Yang · Suhan Cui · Liwei Che · Lingjuan Lyu · Dongkuan (DK) Xu · Fenglong Ma

Mechanic: A Learning Rate Tuner

Ashok Cutkosky · Aaron Defazio · Harsh Mehta

Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception

Hassan Akbari · Dan Kondratyuk · Yin Cui · Rachel Hornung · Huisheng Wang · Hartwig Adam

FAMO: Fast Adaptive Multitask Optimization

Bo Liu · Yihao Feng · Peter Stone · Qiang Liu

Personalized Dictionary Learning for Heterogeneous Datasets

Geyu Liang · Naichen Shi · Raed AL Kontar · Salar Fattahi

Closing the gap between the upper bound and lower bound of Adam's iteration complexity

Bohan Wang · Jingwen Fu · Huishuai Zhang · Nanning Zheng · Wei Chen

Convergence of Adam Under Relaxed Assumptions

Haochuan Li · Alexander Rakhlin · Ali Jadbabaie

Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs

Lin Yang · Junlong Lyu · Wenlong Lyu · Zhitang Chen

Outlier-Robust Wasserstein DRO

Sloan Nietert · Ziv Goldfeld · Soroosh Shafiee

Knowledge Distillation Performs Partial Variance Reduction

Mher Safaryan · Alexandra Peste · Alexandra Peste · Dan Alistarh · Dan Alistarh

Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions

Sayantan Choudhury · Eduard Gorbunov · Nicolas Loizou

PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning

Neeratyoy Mallik · Edward Bergman · Carl Hvarfner · Danny Stoll · Maciej Janowski · Marius Lindauer · Luigi Nardi · Frank Hutter

Robust Bayesian Satisficing

Artun Saday · Y. Cahit Yıldırım · Cem Tekin

MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning

Zeyuan Ma · Hongshu Guo · Jiacheng Chen · Zhenrui Li · Guojun Peng · Yue-Jiao Gong · Yining Ma · Zhiguang Cao

Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation

Myong Chol Jung · He Zhao · Joanna Dipnall · Lan Du

Generalized Information-theoretic Multi-view Clustering

Weitian Huang · Sirui Yang · Hongmin Cai

ContinuAR: Continuous Autoregression For Infinite-Fidelity Fusion

WEI XING · Yuxin Wang · Zheng Xing

Physics-Informed Bayesian Optimization of Variational Quantum Circuits

Kim Nicoli · Christopher J. Anders · Lena Funcke · Tobias Hartung · Karl Jansen · Stefan Kühn · Klaus-Robert Müller · Paolo Stornati · Pan Kessel · Shinichi Nakajima

Conditional score-based diffusion models for Bayesian inference in infinite dimensions

Lorenzo Baldassari · Ali Siahkoohi · Josselin Garnier · Knut Solna · Maarten V. de Hoop

Intrinsic Gaussian Process on Unknown Manifolds with Probabilistic Metrics

mu niu · Zhenwen Dai · Pokman Cheung · Yizhu Wang

Credal Marginal MAP

Radu Marinescu · Debarun Bhattacharjya · Junkyu Lee · Fabio Cozman · Alexander Gray

Quasi-Monte Carlo Graph Random Features

Isaac Reid · Krzysztof M Choromanski · Adrian Weller

Stein $\Pi$-Importance Sampling

Congye Wang · Ye Chen · Heishiro Kanagawa · Chris Oates

The Graph Pencil Method: Mapping Subgraph Densities to Stochastic Block Models

Lee Gunderson · Gecia Bravo-Hermsdorff · Peter Orbanz

Sparse Graph Learning from Spatiotemporal Time Series

Andrea Cini · Daniele Zambon · Cesare Alippi

A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing

Junren Chen · Jonathan Scarlett · Michael Ng · Zhaoqiang Liu

Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback

Marcel Torne Villasevil · Max Balsells I Pamies · Zihan Wang · Samedh Desai · Tao Chen · Pulkit Agrawal · Abhishek Gupta

Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards

Silviu Pitis

Efficient Symbolic Policy Learning with Differentiable Symbolic Expression

Jiaming Guo · Rui Zhang · Shaohui Peng · Qi Yi · Xing Hu · Ruizhi Chen · Zidong Du · xishan zhang · Ling Li · Qi Guo · Yunji Chen

Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation

Ruida Zhou · Tao Liu · Min Cheng · Dileep Kalathil · P. R. Kumar · Chao Tian

Semantic HELM: A Human-Readable Memory for Reinforcement Learning

Fabian Paischer · Thomas Adler · Markus Hofmarcher · Sepp Hochreiter

Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis

Alexander Meulemans · Simon Schug · Seijin Kobayashi · nathaniel daw · Gregory Wayne

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks

Maxime Chevalier-Boisvert · Bolun Dai · Mark Towers · Rodrigo Perez-Vicente · Lucas Willems · Salem Lahlou · Suman Pal · Pablo Samuel Castro · J Terry

Katakomba: Tools and Benchmarks for Data-Driven NetHack

Vladislav Kurenkov · Alexander Nikulin · Denis Tarasov · Sergey Kolesnikov

SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations

Youngsoo Jang · Geon-Hyeong Kim · Jongmin Lee · Sungryull Sohn · Byoungjip Kim · Honglak Lee · Moontae Lee

Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks

Yun Qu · Boyuan Wang · Jianzhun Shao · Yuhang Jiang · Chen Chen · Zhenbin Ye · Liu Linc · Yang Feng · Lin Lai · Hongyang Qin · Minwen Deng · Juchao Zhuo · Deheng Ye · Qiang Fu · YANG GUANG · Wei Yang · Lanxiao Huang · Xiangyang Ji

Offline RL with Discrete Proxy Representations for Generalizability in POMDPs

Pengjie Gu · Xinyu Cai · Dong Xing · Xinrun Wang · Mengchen Zhao · Mengchen Zhao · Bo An

CEIL: Generalized Contextual Imitation Learning

Jinxin Liu · Li He · Yachen Kang · Zifeng Zhuang · Donglin Wang · Huazhe Xu

Survival Instinct in Offline Reinforcement Learning

Anqi Li · Dipendra Misra · Andrey Kolobov · Ching-An Cheng

Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models

Siyan Zhao · Aditya Grover

Combinatorial Optimization with Policy Adaptation using Latent Space Search

Felix Chalumeau · Shikha Surana · Clément Bonnet · Nathan Grinsztajn · Arnu Pretorius · Alexandre Laterre · Tom Barrett

Pgx: Hardware-Accelerated Parallel Game Simulators for Reinforcement Learning

Sotetsu Koyamada · Shinri Okano · Soichiro Nishimori · Yu Murata · Keigo Habara · Haruka Kita · Shin Ishii

A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning

Florian Felten · Lucas N. Alegre · Ann Nowe · Ana Bazzan · El Ghazali Talbi · Grégoire Danoy · Bruno C. da Silva

Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning

Hongyu Zang · Xin Li · Leiji Zhang · Yang Liu · Baigui Sun · Riashat Islam · Riashat Islam · Remi Tachet des Combes · Romain Laroche

When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment

Tianwei Ni · Michel Ma · Benjamin Eysenbach · Pierre-Luc Bacon

Generalized Weighted Path Consistency for Mastering Atari Games

Dengwei Zhao · Shikui Tu · Lei Xu

Self-Supervised Reinforcement Learning that Transfers using Random Features

Boyuan Chen · Chuning Zhu · Pulkit Agrawal · Kaiqing Zhang · Abhishek Gupta

Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization

Nathan Grinsztajn · Daniel Furelos-Blanco · Shikha Surana · Clément Bonnet · Tom Barrett

Belief Projection-Based Reinforcement Learning for Environments with Delayed Feedback

Jangwon Kim · Hangyeol Kim · Jiwook Kang · Jongchan Baek · Soohee Han

RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization

Zhecheng Yuan · Sizhe Yang · Pu Hua · Can Chang · Kaizhe Hu · Huazhe Xu

Small batch deep reinforcement learning

Johan Obando Ceron · Marc Bellemare · Pablo Samuel Castro

NetHack is Hard to Hack

Ulyana Piterbarg · Lerrel Pinto · Rob Fergus

BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset

Jiaming Ji · Mickel Liu · Josef Dai · Xuehai Pan · Chi Zhang · Ce Bian · Boyuan Chen · Ruiyang Sun · Yizhou Wang · Yaodong Yang

Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion

Taehyun Cho · Seungyub Han · Heesoo Lee · Kyungjae Lee · Jungwoo Lee

Ignorance is Bliss: Robust Control via Information Gating

Manan Tomar · Riashat Islam · Riashat Islam · Matthew Taylor · Sergey Levine · Philip Bachman

CQM: Curriculum Reinforcement Learning with a Quantized World Model

Seungjae Lee · Daesol Cho · Jonghae Park · H. Jin Kim

Rewiring Neurons in Non-Stationary Environments

Zhicheng Sun · Yadong Mu

A Robust and Opponent-Aware League Training Method for StarCraft II

Ruozi Huang · Xipeng Wu · Hongsheng Yu · Zhong Fan · Haobo Fu · Qiang Fu · Wei Yang

Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning

Mathias Lechner · lianhao yin · Tim Seyde · Tsun-Hsuan Johnson Wang · Wei Xiao · Ramin Hasani · Joshua Rountree · Daniela Rus

OFCOURSE: A Multi-Agent Reinforcement Learning Environment for Order Fulfillment

Yiheng Zhu · Yang Zhan · Xuankun Huang · Yuwei Chen · yujie Chen · Jiangwen Wei · Wei Feng · Yinzhi Zhou · Haoyuan Hu · Jieping Ye

Hierarchical Multi-Agent Skill Discovery

Mingyu Yang · Yaodong Yang · Zhenbo Lu · Wengang Zhou · Houqiang Li

Tracr: Compiled Transformers as a Laboratory for Interpretability

David Lindner · Janos Kramar · Sebastian Farquhar · Matthew Rahtz · Tom McGrath · Vladimir Mikulik

GEX: A flexible method for approximating influence via Geometric Ensemble

SungYub Kim · Kyungsu Kim · Eunho Yang

Robust Data Valuation with Weighted Banzhaf Values

Weida Li · Yaoliang Yu

What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization

Hao Sun · Boris van Breugel · Jonathan Crabbé · Nabeel Seedat · Mihaela van der Schaar

The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks

Ziqian Zhong · Ziming Liu · Max Tegmark · Jacob Andreas

Error Discovery By Clustering Influence Embeddings

Fulton Wang · Julius Adebayo · Julius Adebayo · Sarah Tan · Diego Garcia-Olano · Narine Kokhlikyan

DISCOVER: Making Vision Networks Interpretable via Competition and Dissection

Konstantinos Panousis · Sotirios Chatzis

[Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles

Kyosuke Morita

Building Socio-culturally Inclusive Stereotype Resources with Community Engagement

Sunipa Dev · Jaya Goyal · Dinesh Tewari · Shachi Dave · Vinodkumar Prabhakaran

Doubly Constrained Fair Clustering

John Dickerson · Seyed Esmaeili · Jamie Morgenstern · Claire Jie Zhang

GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition

Vikram V. Ramaswamy · Sing Yu Lin · Dora Zhao · Aaron Adcock · Laurens van der Maaten · Deepti Ghadiyaram · Olga Russakovsky

Scalable Fair Influence Maximization

Xiaobin Rui · Zhixiao Wang · Jiayu Zhao · Lichao Sun · Wei Chen

Fair Graph Distillation

Qizhang Feng · Zhimeng (Stephen) Jiang · Ruiquan Li · Yicheng Wang · Na Zou · Jiang Bian · Xia Hu

VisoGender: A dataset for benchmarking gender bias in image-text pronoun resolution

Siobhan Mackenzie Hall · Fernanda Gonçalves Abrantes · Hanwen Zhu · Grace Sodunke · Aleksandar Shtedritski · Hannah Rose Kirk

DICES Dataset: Diversity in Conversational AI Evaluation for Safety

Lora Aroyo · Alex Taylor · Mark Díaz · Christopher Homan · Alicia Parrish · Gregory Serapio-García · Vinodkumar Prabhakaran · Ding Wang

Into the LAION’s Den: Investigating Hate in Multimodal Datasets

Abeba Birhane · vinay prabhu · Sanghyun Han · Vishnu Boddeti · Sasha Luccioni

Dream the Impossible: Outlier Imagination with Diffusion Models

Xuefeng Du · Yiyou Sun · Jerry Zhu · Yixuan Li

Consensus and Subjectivity of Skin Tone Annotation for ML Fairness

Candice Schumann · Femi Olanubi · Auriel Wright · Ellis Monk · Courtney Heldreth · Susanna Ricco

Diverse Community Data for Benchmarking Data Privacy Algorithms

Aniruddha Sen · Christine Task · Dhruv Kapur · Gary Howarth · Karan Bhagat

(Amplified) Banded Matrix Factorization: A unified approach to private training

Christopher A. Choquette-Choo · Arun Ganesh · Ryan McKenna · H. Brendan McMahan · John Rush · Abhradeep Guha Thakurta · Zheng Xu

Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models

Haonan Duan · Adam Dziedzic · Nicolas Papernot · Franziska Boenisch

What Can We Learn from Unlearnable Datasets?

Pedro Sandoval-Segura · Vasu Singla · Jonas Geiping · Micah Goldblum · Tom Goldstein

Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition

Yiting Dong · Yang Li · Dongcheng Zhao · Guobin Shen · Yi Zeng

Counting Distinct Elements Under Person-Level Differential Privacy

Thomas Steinke · Alexander Knop

Understanding Deep Gradient Leakage via Inversion Influence Functions

Haobo Zhang · Junyuan Hong · Yuyang Deng · Mehrdad Mahdavi · Jiayu Zhou

Sparsity-Preserving Differentially Private Training of Large Embedding Models

Badih Ghazi · Yangsibo Huang · Pritish Kamath · Ravi Kumar · Pasin Manurangsi · Amer Sinha · Chiyuan Zhang

Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense

Zhiyuan Zhang · Deli Chen · Hao Zhou · Fandong Meng · Jie Zhou · Xu Sun

VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception

Jiyoung Lee · Seungho Kim · Seunghyun Won · Joonseok Lee · Marzyeh Ghassemi · James Thorne · Jaeseok Choi · O-Kil Kwon · Edward Choi

Static and Sequential Malicious Attacks in the Context of Selective Forgetting

Chenxu Zhao · Wei Qian · Rex Ying · Mengdi Huai

Proximity-Informed Calibration for Deep Neural Networks

Miao Xiong · Ailin Deng · Pang Wei Koh · Jiaying Wu · Shen Li · Jianqing Xu · Bryan Hooi

Understanding the detrimental class-level effects of data augmentation

Polina Kirichenko · Mark Ibrahim · Randall Balestriero · Diane Bouchacourt · Shanmukha Ramakrishna Vedantam · Hamed Firooz · Andrew Wilson

Automated Classification of Model Errors on ImageNet

Momchil Peychev · Mark Müller · Marc Fischer · Martin Vechev

Multi-scale Diffusion Denoised Smoothing

Jongheon Jeong · Jinwoo Shin

Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples

Shaokui Wei · Mingda Zhang · Hongyuan Zha · Baoyuan Wu

Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond

Anna Hedström · Leander Weber · Daniel Krakowczyk · Dilyara Bareeva · Franz Motzkus · Wojciech Samek · Sebastian Lapuschkin · Marina Höhne

A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)

Weijie Tu · Weijian Deng · Tom Gedeon

Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective

Yifei Wang · Liangchen Li · Jiansheng Yang · Zhouchen Lin · Yisen Wang

Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization

Xilie Xu · Jingfeng ZHANG · Feng Liu · Masashi Sugiyama · Mohan Kankanhalli

D-Separation for Causal Self-Explanation

Wei Liu · Jun Wang · Haozhao Wang · Ruixuan Li · Zhiying Deng · YuanKai Zhang · Yang Qiu

DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection

Zhiyuan Yan · Yong Zhang · Xinhang Yuan · Siwei Lyu · Baoyuan Wu

On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets

Jiashuo Liu · Tianyu Wang · Peng Cui · Hongseok Namkoong

Jailbroken: How Does LLM Safety Training Fail?

Alexander Wei · Nika Haghtalab · Jacob Steinhardt

Active Learning for Semantic Segmentation with Multi-class Label Query

Sehyun Hwang · Sohyun Lee · Hoyoung Kim · Minhyeon Oh · Jungseul Ok · Suha Kwak

Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions

Leonidas Tsepenekas · Ivan Brugere · Freddy Lecue · Daniele Magazzeni

MADG: Margin-based Adversarial Learning for Domain Generalization

Aveen Dayal · Vimal K B · Linga Reddy Cenkeramaddi · C Mohan · Abhinav Kumar · Vineeth N Balasubramanian

Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset

Saeid Alavi Naeini · Raeid Saqur · Mozhgan Saeidi · John Giorgi · Babak Taati

Fitting trees to $\ell_1$-hyperbolic distances

Joon-Hyeok Yim · Anna Gilbert

Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods

Shang Liu · Zhongze Cai · Xiaocheng Li

Exponential Lower Bounds for Fictitious Play in Potential Games

Ioannis Panageas · Nikolas Patris · Stratis Skoulakis · Volkan Cevher

Higher-Order Uncoupled Dynamics Do Not Lead to Nash Equilibrium - Except When They Do

Sarah Toonsi · Jeff Shamma

Calibrating “Cheap Signals” in Peer Review without a Prior

Yuxuan Lu · Yuqing Kong

Mechanism Design for Collaborative Normal Mean Estimation

Yiding Chen · Jerry Zhu · Kirthevasan Kandasamy

Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games

Brian Zhang · Gabriele Farina · Ioannis Anagnostides · Federico Cacciamani · Stephen McAleer · Andreas Haupt · Andrea Celli · Nicola Gatti · Vincent Conitzer · Tuomas Sandholm

New Complexity-Theoretic Frontiers of Tractability for Neural Network Training

Cornelius Brand · Robert Ganian · Mathis Rocton

Tester-Learners for Halfspaces: Universal Algorithms

Aravind Gollakota · Adam Klivans · Konstantinos Stavropoulos · Arsen Vasilyan

Adversarial Resilience in Sequential Prediction via Abstention

Surbhi Goel · Steve Hanneke · Shay Moran · Abhishek Shetty

Stability of Random Forests and Coverage of Random-Forest Prediction Intervals

Yan Wang · Huaiqing Wu · Dan Nettleton

The Bayesian Stability Zoo

Shay Moran · Hilla Schefler · Jonathan Shafer

Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance

Lisha Chen · Heshan Fernando · Yiming Ying · Tianyi Chen

Collaboratively Learning Linear Models with Structured Missing Data

Chen Cheng · Gary Cheng · John Duchi

Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension

Moritz Haas · David Holzmüller · Ulrike Luxburg · Ingo Steinwart

Random Cuts are Optimal for Explainable k-Medians

Konstantin Makarychev · Liren Shan

Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models

Dat Do · Huy Nguyen · Khai Nguyen · Nhat Ho

Provable benefits of score matching

Chirag Pabbaraju · Dhruv Rohatgi · Anish Prasad Sevekari · Holden Lee · Ankur Moitra · Andrej Risteski

Multiclass Boosting: Simple and Intuitive Weak Learning Criteria

Nataly Brukhim · Amit Daniely · Yishay Mansour · Shay Moran

The Geometry of Neural Nets' Parameter Spaces Under Reparametrization

Agustinus Kristiadi · Felix Dangel · Philipp Hennig

Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures

Hamish Flynn · David Reeb · Melih Kandemir · Jan Peters

Online Corrupted User Detection and Regret Minimization

Zhiyong Wang · Jize Xie · Tong Yu · Shuai Li · John C.S. Lui

Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards

Hao Qin · Kwang-Sung Jun · Chicheng Zhang

Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference

Licong Lin · Mufang Ying · Suvrojit Ghosh · Koulik Khamaru · Cun-Hui Zhang

Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework

Ziyi Huang · Henry Lam · Amirhossein Meisami · Haofeng Zhang

Adaptive Algorithms for Relaxed Pareto Set Identification

Cyrille KONE · Emilie Kaufmann · Laura Richert

Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness

Evgenii Chzhen · Christophe Giraud · Zhen LI · Gilles Stoltz

Non-Stationary Bandits with Auto-Regressive Temporal Dependency

Qinyi Chen · Negin Golrezaei · Djallel Bouneffouf

Adaptive Linear Estimating Equations

Mufang Ying · Koulik Khamaru · Cun-Hui Zhang

Exploiting Correlated Auxiliary Feedback in Parameterized Bandits

Arun Verma · Zhongxiang Dai · Zhongxiang Dai · YAO SHU · Bryan Kian Hsiang Low

An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits

Shinji Ito · Kei Takemura

Covariance-adaptive best arm identification

El Mehdi Saad · Gilles Blanchard · Nicolas Verzelen

Online List Labeling with Predictions

Samuel McCauley · Ben Moseley · Aidin Niaparast · Shikha Singh

The Separation Capacity of Random Neural Networks

Sjoerd Dirksen · Martin Genzel · Laurent Jacques · Alexander Stollenwerk

Concentration analysis of multivariate elliptic diffusions

Lukas Trottner · Cathrine Aeckerle-Willems · Claudia Strauch

Conditional Distribution Function Estimation Using Neural Networks for Censored and Uncensored Data

Bingqing Hu · Bin Nan

Is RLHF More Difficult than Standard RL? A Theoretical Perspective

Yuanhao Wang · Qinghua Liu · Chi Jin

Bridging RL Theory and Practice with the Effective Horizon

Cassidy Laidlaw · Stuart J Russell · Anca Dragan

Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL

Qinghua Liu · Gellert Weisz · András György · Chi Jin · Csaba Szepesvari

Replicable Reinforcement Learning

Eric Eaton · Marcel Hussing · Michael Kearns · Jessica Sorrell

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond

Thanh Nguyen-Tang · Raman Arora

A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence

Carlo Alfano · Rui Yuan · Rui Yuan · Patrick Rebeschini

Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

Fan Yao · Chuanhao Li · Karthik Abinav Sankararaman · Yiming Liao · Yan Zhu · Qifan Wang · Hongning Wang · Haifeng Xu

[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization

Luka Žontar

[Re] On Explainability of Graph Neural Networks via Subgraph Explorations

Yannik Mahlau · Lukas Berg · Leonie Kayser

[Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification

Ermin Omeragic · Vuk Đuranović

[Re] End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking

Sean McLeish · Long Tran-Thanh

[Re] Fairness Guarantees under Demographic Shift

Valentin Buchner · Philip Schutte · Yassin Ben Allal · Hamed Ahadi

[Re] Numerical influence of ReLU'(0) on backpropagation

Tommaso Martorella · Hector Manuel Ramirez Contreras · Daniel Garcia

Reproducibility Study of ”Label-Free Explainability for Unsupervised Models”

Julius Wagenbach · Gergely Papp · Niklas Mather · Laurens de Vries

$\mathbf{\mathbb{E}^{FWI}}$: Multiparameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties

Shihang Feng · Hanchen Wang · Chengyuan Deng · Yinan Feng · Yanhua Liu · Min Zhu · Peng Jin · Yinpeng Chen · Youzuo Lin

RELIC: Reproducibility and Extension on LIC metric in quantifying bias in captioning models

Martijn van Raaphorst · Egoitz Gonzalez · Marta Grasa · Paula Antequera Hernández

[Re] CrossWalk: Fairness-enhanced Node Representation Learning

Luca Pantea · Andrei-Eusebiu Blahovici

[Re] Pure Noise to the Rescue of Insufficient Data

Ryan Lee · Seungmin Lee

Evaluating Open-QA Evaluation

Cunxiang Wang · Sirui Cheng · Qipeng Guo · Yuanhao Yue · Bowen Ding · Zhikun Xu · Yidong Wang · Xiangkun Hu · Zheng Zhang · Yue Zhang

On the Importance of Exploration for Generalization in Reinforcement Learning

Yiding Jiang · J. Zico Kolter · Roberta Raileanu

RealTime QA: What's the Answer Right Now?

Jungo Kasai · Keisuke Sakaguchi · yoichi takahashi · Ronan Le Bras · Akari Asai · Xinyan Yu · Dragomir Radev · Noah Smith · Yejin Choi · Kentaro Inui

Weakly-Supervised Audio-Visual Segmentation

Shentong Mo · Shentong Mo · Bhiksha Raj

Structured Voronoi Sampling

Afra Amini · Li Du · Ryan Cotterell

Optimal Learners for Realizable Regression: PAC Learning and Online Learning

Idan Attias · Steve Hanneke · Alkis Kalavasis · Amin Karbasi · Grigoris Velegkas

Ambient Diffusion: Learning Clean Distributions from Corrupted Data

Giannis Daras · Kulin Shah · Yuval Dagan · Aravind Gollakota · Alex Dimakis · Adam Klivans

Granger Components Analysis: Unsupervised learning of latent temporal dependencies

Jacek Dmochowski

VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models

Sheng-Yen Chou · Pin-Yu Chen · Tsung-Yi Ho

FedNAR: Federated Optimization with Normalized Annealing Regularization

Junbo Li · Ang Li · Chong Tian · Qirong Ho · Eric Xing · Hongyi Wang

Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis

Dachao Lin · Yuze Han · Haishan Ye · Zhihua Zhang

ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints

Anikait Singh · Aviral Kumar · Quan Vuong · Yevgen Chebotar · Sergey Levine

Optimized Covariance Design for AB Test on Social Network under Interference

Qianyi Chen · Bo Li · Lu Deng · Yong Wang

Easy Bayesian Transfer Learning with Informative Priors

Martin Špendl · Klementina Pirc

SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning

Benjamin Ellis · Jonathan Cook · Skander Moalla · Mikayel Samvelyan · Mingfei Sun · Anuj Mahajan · Jakob Foerster · Shimon Whiteson

Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion

weitao Du · Jiujiu Chen · Xuecang Zhang · Zhi-Ming Ma · Shengchao Liu

Reproducibility Study of “Quantifying Societal Bias Amplification in Image Captioning”

Farrukh Baratov · Goksenin Yuksel · Darie Petcu · Jan Bakker

P-Flow: A Fast and Data-Efficient Zero-Shot TTS through Speech Prompting

Sungwon Kim · Kevin Shih · rohan badlani · Joao Felipe Santos · Evelina Bakhturina · Mikyas Desta · Rafael Valle · Sungroh Yoon · Bryan Catanzaro

Color Equivariant Convolutional Networks

Attila Lengyel · Ombretta Strafforello · Robert-Jan Bruintjes · Alexander Gielisse · Jan van Gemert

Spatial-frequency channels, shape bias, and adversarial robustness

Ajay Subramanian · Elena Sizikova · Najib Majaj · Denis Pelli

[Re] On the Reproducibility of CartoonX

Robin Sasse · Aniek Eijpe · Jona Ruthardt · Elias Dubbeldam

Optimal Algorithms for the Inhomogeneous Spiked Wigner Model

Aleksandr Pak · Justin Ko · Justin Ko · Florent Krzakala

[Re] Exploring the Role of Grammar and Word Choice in Bias Toward African American English (AAE) in Hate Speech Classification

Priyanka Bose · Chandra Shekhar Pandey · Fraida Fund

Inference for Gaussian Processes with Matern Covariogram on Compact Riemannian Manifolds

Didong Li · Wenpin Tang · Sudipto Banerjee

MLFMF: Data Sets for Machine Learning for Mathematical Formalization

Andrej Bauer · Matej Petković · Ljupco Todorovski

Scalable Membership Inference Attacks via Quantile Regression

Martin Bertran · Shuai Tang · Aaron Roth · Michael Kearns · Jamie Morgenstern · Steven Wu

Generating QM1B with PySCF$_{\text{IPU}}$

Alexander Mathiasen · Hatem Helal · Kerstin Klaser · Paul Balanca · Josef Dean · Carlo Luschi · Dominique Beaini · Andrew Fitzgibbon · Dominic Masters

Online robust non-stationary estimation

Abishek Sankararaman · Balakrishnan Narayanaswamy

Learning from Rich Semantics and Coarse Locations for Long-tailed Object Detection

Lingchen Meng · Xiyang Dai · Jianwei Yang · Dongdong Chen · Yinpeng Chen · Yinpeng Chen · Mengchen Liu · Yi-Ling Chen · Zuxuan Wu · Lu Yuan · Yu-Gang Jiang

Progressive Ensemble Distillation: Building Ensembles for Efficient Inference

Don Dennis · Abhishek Shetty · Anish Prasad Sevekari · Kazuhito Koishida · Virginia Smith

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning

Joseph Suarez · David Bloomin · Kyoung Whan Choe · Hao Xiang Li · Ryan Sullivan · Nishaanth Kanna · Daniel Scott · Rose Shuman · Herbie Bradley · Louis Castricato · Phillip Isola · Chenghui Yu · Yuhao Jiang · Qimai Li · Jiaxin Chen · Xiaolong Zhu

[Re] On the Reproducibility of “FairCal: Fairness Calibration for Face Verification”

Marga Don · Satchit Chatterji · Milena Kapralova · Ryan Amaudruz

Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events

Matthew McDermott · Bret Nestor · Peniel Argaw · Isaac S Kohane

$\mathcal{M}^4$: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models

Xuhong Li · Mengnan Du · Jiamin Chen · Yekun Chai · Himabindu Lakkaraju · Haoyi Xiong

Thin and deep Gaussian processes

Daniel Augusto de Souza · Alexander Nikitin · ST John · Magnus Ross · Mauricio A Álvarez · Marc Deisenroth · João Paulo Gomes · Diego Mesquita · César Lincoln Mattos

Reproducibility study of the Fairness-enhanced Node Representation Learning

Gijs Moens · Job De Witte · Tobias Gobel · Meggie Van den Oever

When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Duncan McElfresh · Sujay Khandagale · Jonathan Valverde · Vishak Prasad C · Ganesh Ramakrishnan · Micah Goldblum · Colin White

[Re] Variational Neural Cellular Automata

Albert Sund Aillet · Simon Sondén

Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network

Fuyuan Lyu · Xing Tang · Dugang Liu · Chen Ma · Weihong Luo · Liang Chen · xiuqiang He · Xue (Steve) Liu

Go to Event Page

Town Hall

Terry Sejnowski · Tristan Naumann · Alice Oh

7:00 PM - 8:00 PM

Creative AI Performances 2

Jean Oh · Isabelle Guyon

7:00 PM - 9:00 PM

7 Events in this session

Resonator: An AI-assisted Musical Experience for Human Connection

Erin Drake Kajioka

Emergent Rhythm — Real-time AI Generative DJ Set

Nao Tokui

Entanglement

Fusion: Landscape and Beyond

Mingyong Cheng · Xuexi Dang · Zetao Yu · Xingwen Zhao

Kiss/Crash

The WHOOPS! Gallery: An Intersection of AI, Creativity, and the Unusual

Collaborative Synthscapes from Words

Nikhil Singh · Manuel Cherep · Jessica Shand

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Reception

Closing Reception

8:00 PM - 9:00 PM