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Timezone: America/Chicago
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Registration Desk
7:30 AM - 6:00 PM
Invited Talk
8:30 AM - 9:20 AM

Conventional machine learning paradigms often rely on binary distinctions between positive and negative examples, disregarding the nuanced subjectivity that permeates real-world tasks and content. This simplistic dichotomy has served us well so far, but because it obscures the inherent diversity in human perspectives and opinions, as well as the inherent ambiguity of content and tasks, it poses limitations on model performance aligned with real-world expectations. This becomes even more critical when we study the impact and potential multifaceted risks associated with the adoption of emerging generative AI capabilities across different cultures and geographies. To address this, we argue that to achieve robust and responsible AI systems we need to shift our focus away from a single point of truth and weave in a diversity of perspectives in the data used by AI systems to ensure the trust, safety and reliability of model outputs.

In this talk, I present a number of data-centric use cases that illustrate the inherent ambiguity of content and natural diversity of human perspectives that cause unavoidable disagreement that needs to be treated as signal and not noise. This leads to a call for action to establish culturally-aware and society-centered research on impacts of data quality and data diversity for the purposes of training and evaluating ML models and fostering responsible AI deployment in diverse sociocultural contexts.

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Speaker Bio
Lora Aroyo
I am a research scientist at Google DeepMind NYC where I work on Data Excellence for AI. My team DEER (Data Excellence for Evaluating Responsibly) is part of the Responsible AI (RAI) organization. Our work is focused on developing metrics and methodologies to measure the quality of human-labeled or machine-generated data. The specific scope of this work is for gathering and evaluation of adversarial data for Safety evaluation of Generative AI systems. I received MSc in Computer Science from Sofia University, Bulgaria, and PhD from Twente University, The Netherlands. I am currently serving as a co-chair of the steering committee for the AAAI HCOMP conference series and I am a member of the DataPerf working group at MLCommons for benchmarking data-centric AI. Check out our data-centric challenge Adversarial Nibbler supported by Kaggle, Hugging Face and MLCommons. Prior to joining Google, I was a computer science professor heading the User-Centric Data Science research group at the VU University Amsterdam. Our team invented the CrowdTruth crowdsourcing method jointly with the Watson team at IBM. This method has been applied in various domains such as digital humanities, medical and online multimedia. I also guided the human-in-the-loop strategies as a Chief Scientist at a NY-based startup Tagasauris. Some of my prior community contributions include president of the User Modeling Society, program co-chair of The Web Conference 2023, member of the ACM SIGCHI conferences board. For a list of my publications, please see my profile on Google Scholar.
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Oral
10:00 AM - 10:45 AM
3 Events in this session
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Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach
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Characteristic Circuits
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Oral
10:00 AM - 10:45 AM
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Abide by the law and follow the flow: conservation laws for gradient flows
Sibylle Marcotte · Remi Gribonval · Gabriel Peyré
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning
Alicia Curth · Alan Jeffares · Mihaela van der Schaar
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Oral
10:00 AM - 10:45 AM
3 Events in this session
Ordering-based Conditions for Global Convergence of Policy Gradient Methods
Jincheng Mei · Bo Dai · Alekh Agarwal · Mohammad Ghavamzadeh · Csaba Szepesvari · Dale Schuurmans
When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
Siliang Zeng · Chenliang Li · Alfredo Garcia · Mingyi Hong
Online RL in Linearly $q^\pi$-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore
Gellert Weisz · András György · Csaba Szepesvari
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Oral
10:00 AM - 10:45 AM
3 Events in this session
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
Kaiyu Yang · Aidan Swope · Alex Gu · Rahul Chalamala · Peiyang Song · Shixing Yu · Saad Godil · Ryan J Prenger · Animashree Anandkumar
OpenAssistant Conversations - Democratizing Large Language Model Alignment
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DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
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Poster
10:45 AM - 12:45 PM
599 Events in this session
PIXIU: A Comprehensive Benchmark, Instruction Dataset and Large Language Model for Finance
Qianqian Xie · Weiguang Han · Xiao Zhang · Yanzhao Lai · Min Peng · Alejandro Lopez-Lira · Jimin Huang
FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation
Yuanxin Liu · Lei Li · Shuhuai Ren · Rundong Gao · Shicheng Li · Sishuo Chen · Xu Sun · Lu Hou
Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking
Mohammad Mahdi Kamani · Yuhang Yao · Hanjia Lyu · Zhongwei Cheng · Lin Chen · Liangju Li · Carlee Joe-Wong · Jiebo Luo
ChessGPT: Bridging Policy Learning and Language Modeling
Xidong Feng · Yicheng Luo · Ziyan Wang · Hongrui Tang · Mengyue Yang · Kun Shao · David Mguni · Yali Du · Jun Wang
EMBERSim: A Large-Scale Databank for Boosting Similarity Search in Malware Analysis
Dragos Georgian Corlatescu · Alexandru Dinu · Mihaela Petruta Gaman · Paul Sumedrea
AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems
Jeroen Berrevoets · Daniel Jarrett · Alex Chan · Mihaela van der Schaar
Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering
Tianxiao Li · Hongyu Guo · Filippo Grazioli · Mark Gerstein · Martin Renqiang Min
Fragment-based Pretraining and Finetuning on Molecular Graphs
Kha-Dinh Luong · Ambuj K Singh
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction
Zuobai Zhang · Minghao Xu · Aurelie Lozano · Vijil Chenthamarakshan · Payel Das · Jian Tang
AbDiffuser: full-atom generation of in-vitro functioning antibodies
Karolis Martinkus · Jan Ludwiczak · WEI-CHING LIANG · Julien Lafrance-Vanasse · Isidro Hotzel · Arvind Rajpal · Yan Wu · Kyunghyun Cho · Richard Bonneau · Vladimir Gligorijevic · Andreas Loukas
Predicting mutational effects on protein-protein binding via a side-chain diffusion probabilistic model
Shiwei Liu · Tian Zhu · Milong Ren · Chungong Yu · Dongbo Bu · Haicang Zhang
Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer
Namkyeong Lee · Heewoong Noh · Sungwon Kim · Dongmin Hyun · Gyoung S. Na · Chanyoung Park
Smooth, exact rotational symmetrization for deep learning on point clouds
Sergey Pozdnyakov · Michele Ceriotti
AirDelhi: Fine-Grained Spatio-Temporal Particulate Matter Dataset From Delhi For ML based Modeling
Sachin Chauhan · Zeel Bharatkumar Patel · Sayan Ranu · Rijurekha Sen · Nipun Batra
SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking
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OceanBench: The Sea Surface Height Edition
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M5HisDoc: A Large-scale Multi-style Chinese Historical Document Analysis Benchmark
Yongxin Shi · Chongyu Liu · Dezhi Peng · Cheng Jian · Jiarong Huang · Lianwen Jin
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
Julia Kaltenborn · Charlotte Lange · Venkatesh Ramesh · Philippe Brouillard · Yaniv Gurwicz · Chandni Nagda · Jakob Runge · Peer Nowack · David Rolnick
HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge Understanding
Hao Zheng · Regina Lee · Yuqian Lu
DVSOD: RGB-D Video Salient Object Detection
Jingjing Li · Wei Ji · Size Wang · Wenbo Li · Li cheng
Hierarchical Open-vocabulary Universal Image Segmentation
Xudong Wang · Shufan Li · Konstantinos Kallidromitis · Yusuke Kato · Kazuki Kozuka · Trevor Darrell
FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models
Lihe Yang · Xiaogang Xu · Bingyi Kang · Yinghuan Shi · Hengshuang Zhao
Query-based Temporal Fusion with Explicit Motion for 3D Object Detection
Jinghua Hou · Zhe Liu · dingkang liang · Zhikang Zou · Xiaoqing Ye · Xiang Bai
Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning
Changsheng Lv · Shuai Zhang · Yapeng Tian · Mengshi Qi · Huadong Ma
Zero-shot Visual Relation Detection via Composite Visual Cues from Large Language Models
Lin Li · Jun Xiao · Guikun Chen · Jian Shao · Yueting Zhuang · Long Chen
VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models
Yonatan Bitton · Hritik Bansal · Jack Hessel · Rulin Shao · Wanrong Zhu · Anas Awadalla · Josh Gardner · Rohan Taori · Ludwig Schmidt
PrObeD: Proactive Object Detection Wrapper
Vishal Asnani · Abhinav Kumar · Suya You · Xiaoming Liu
DreamSparse: Escaping from Plato’s Cave with 2D Diffusion Model Given Sparse Views
Paul Yoo · Jiaxian Guo · Yutaka Matsuo · Shixiang (Shane) Gu
Generalizable One-shot 3D Neural Head Avatar
Xueting Li · Shalini De Mello · Sifei Liu · Koki Nagano · Umar Iqbal · Jan Kautz
Video-Mined Task Graphs for Keystep Recognition in Instructional Videos
Kumar Ashutosh · Santhosh Kumar Ramakrishnan · Triantafyllos Afouras · Kristen Grauman
SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection
Daehyun Kim · Sungyong Baik · Tae Hyun Kim
Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration
Theo Adrai · Guy Ohayon · Michael Elad · Tomer Michaeli
Deep Non-line-of-sight Imaging from Under-scanning Measurements
Yue Li · Yueyi Zhang · Juntian Ye · Feihu Xu · Zhiwei Xiong
ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab
Jieming Cui · Ziren Gong · Baoxiong Jia · Siyuan Huang · Zilong Zheng · Jianzhu Ma · Yixin Zhu
Rewrite Caption Semantics: Bridging Semantic Gaps for Language-Supervised Semantic Segmentation
Yun Xing · Jian Kang · Aoran Xiao · Jiahao Nie · Ling Shao · Shijian Lu
What’s Left? Concept Grounding with Logic-Enhanced Foundation Models
Joy Hsu · Jiayuan Mao · Josh Tenenbaum · Jiajun Wu
Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition
Wei He · Kai Han · Ying Nie · Chengcheng Wang · Yunhe Wang
Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator
Xiaolong Wang · Runsen Xu · Zhuofan Cui · Zeyu Wan · Yu Zhang
Leave No Stone Unturned: Mine Extra Knowledge for Imbalanced Facial Expression Recognition
Yuhang Zhang · Yaqi Li · lixiong Qin · Xuannan Liu · Weihong Deng
Knowledge Diffusion for Distillation
Tao Huang · Yuan Zhang · Mingkai Zheng · Shan You · Fei Wang · Chen Qian · Chang Xu
GenS: Generalizable Neural Surface Reconstruction from Multi-View Images
Rui Peng · Xiaodong Gu · Luyang Tang · Shihe Shen · Fanqi Yu · Ronggang Wang
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection
Cheng-Ju Ho · Chen-Hsuan Tai · Yen-Yu Lin · Ming-Hsuan Yang · Yi-Hsuan Tsai
ConRad: Image Constrained Radiance Fields for 3D Generation from a Single Image
Senthil Purushwalkam · Nikhil Naik
StoryBench: A Multifaceted Benchmark for Continuous Story Visualization
Emanuele Bugliarello · H. Hernan Moraldo · Ruben Villegas · Mohammad Babaeizadeh · Mohammad Taghi Saffar · Han Zhang · Dumitru Erhan · Vittorio Ferrari · Pieter-Jan Kindermans · Paul Voigtlaender
3D Indoor Instance Segmentation in an Open-World
Mohamed El Amine Boudjoghra · Salwa Al Khatib · Jean Lahoud · Hisham Cholakkal · Rao Anwer · Rao Anwer · Salman Khan · Fahad Shahbaz Khan
Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models
Sivan Doveh · Assaf Arbelle · Sivan Harary · Roei Herzig · Donghyun Kim · Paola Cascante-Bonilla · Amit Alfassy · Rameswar Panda · Raja Giryes · Rogerio Feris · Shimon Ullman · Leonid Karlinsky
CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data
Taiki Miyanishi · Fumiya Kitamori · Shuhei Kurita · Jungdae Lee · Motoaki Kawanabe · Nakamasa Inoue
Subject-driven Text-to-Image Generation via Apprenticeship Learning
Wenhu Chen · Hexiang Hu · Yandong Li · Nataniel Ruiz · Xuhui Jia · Ming-Wei Chang · William Cohen
Topological RANSAC for instance verification and retrieval without fine-tuning
Guoyuan An · Ju-hyeong Seon · Inkyu An · Yuchi Huo · Sung-eui Yoon
Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation
Zibo Zhao · Wen Liu · Xin Chen · Xianfang Zeng · Rui Wang · Pei Cheng · BIN FU · Tao Chen · Gang Yu · Shenghua Gao
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
Atsuyuki Miyai · Qing Yu · Go Irie · Kiyoharu Aizawa
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
Dongwei Pan · Long Zhuo · Jingtan Piao · Huiwen Luo · Wei Cheng · Yuxin WANG · Siming Fan · Shengqi Liu · Lei Yang · Bo Dai · Ziwei Liu · Chen Change Loy · Chen Qian · Wayne Wu · Dahua Lin · Kwan-Yee Lin
Aligning Gradient and Hessian for Neural Signed Distance Function
Ruian Wang · Zixiong Wang · Yunxiao Zhang · Shuangmin Chen · Shiqing Xin · Changhe Tu · Wenping Wang
CP-SLAM: Collaborative Neural Point-based SLAM System
Jiarui Hu · Mao Mao · Hujun Bao · Guofeng Zhang · Zhaopeng Cui
STXD: Structural and Temporal Cross-Modal Distillation for Multi-View 3D Object Detection
Sujin Jang · Dae Ung Jo · Sung Ju Hwang · Dongwook Lee · Daehyun Ji
FaceComposer: A Unified Model for Versatile Facial Content Creation
Jiayu Wang · Kang Zhao · Yifeng Ma · Shiwei Zhang · Yingya Zhang · Yujun Shen · Deli Zhao · Jingren Zhou
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization
Minghua Liu · Chao Xu · Haian Jin · Linghao Chen · Mukund Varma T · Zexiang Xu · Hao Su
T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation
Kaiyi Huang · Kaiyue Sun · Enze Xie · Zhenguo Li · Xihui Liu
A Multi-modal Global Instance Tracking Benchmark (MGIT): Better Locating Target in Complex Spatio-temporal and Causal Relationship
Shiyu Hu · Dailing Zhang · wu meiqi · Xiaokun Feng · Xuchen Li · Xin Zhao · Kaiqi Huang
XAGen: 3D Expressive Human Avatars Generation
Zhongcong XU · Jianfeng Zhang · Jun Hao Liew · Jiashi Feng · Mike Zheng Shou
Mr. HiSum: A Large-scale Dataset for Video Highlight Detection and Summarization
Jinhwan Sul · Jihoon Han · Joonseok Lee
Learning to Parameterize Visual Attributes for Open-set Fine-grained Retrieval
Shijie Wang · Jianlong Chang · Haojie Li · Zhihui Wang · Wanli Ouyang · Qi Tian
SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation
Zhongang Cai · Wanqi Yin · Ailing Zeng · CHEN WEI · Qingping SUN · Wang Yanjun · Hui En Pang · Haiyi Mei · Mingyuan Zhang · Lei Zhang · Chen Change Loy · Lei Yang · Ziwei Liu
Online Map Vectorization for Autonomous Driving: A Rasterization Perspective
Gongjie Zhang · Jiahao Lin · Shuang Wu · yilin song · Zhipeng Luo · Yang Xue · Shijian Lu · Zuoguan Wang
Are These the Same Apple? Comparing Images Based on Object Intrinsics
Klemen Kotar · Stephen Tian · Hong-Xing Yu · Dan Yamins · Jiajun Wu
StEik: Stabilizing the Optimization of Neural Signed Distance Functions and Finer Shape Representation
Huizong Yang · Yuxin Sun · Ganesh Sundaramoorthi · Anthony Yezzi
LayoutPrompter: Awaken the Design Ability of Large Language Models
Jiawei Lin · Jiaqi Guo · Shizhao Sun · Zijiang Yang · Jian-Guang Lou · Dongmei Zhang
JourneyDB: A Benchmark for Generative Image Understanding
Keqiang Sun · Junting Pan · Yuying Ge · Hao Li · Haodong Duan · Xiaoshi Wu · Renrui Zhang · Aojun Zhou · Zipeng Qin · Yi Wang · Jifeng Dai · Yu Qiao · Limin Wang · Hongsheng Li
Kiki or Bouba? Sound Symbolism in Vision-and-Language Models
Morris Alper · Hadar Averbuch-Elor
Global Structure-Aware Diffusion Process for Low-light Image Enhancement
Jinhui HOU · Zhiyu Zhu · Junhui Hou · Hui LIU · Huanqiang Zeng · Hui Yuan
A High-Resolution Dataset for Instance Detection with Multi-View Object Capture
QIANQIAN SHEN · Yunhan Zhao · Nahyun Kwon · Jeeeun Kim · Yanan Li · Shu Kong
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text
Wanrong Zhu · Jack Hessel · Anas Awadalla · Samir Yitzhak Gadre · Jesse Dodge · Alex Fang · Youngjae Yu · Ludwig Schmidt · William Yang Wang · Yejin Choi
Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization
Yuxin Guo · Shijie Ma · Hu Su · Zhiqing Wang · Yuhao Zhao · Wei Zou · Siyang Sun · Yun Zheng
OpenIllumination: A Multi-Illumination Dataset for Inverse Rendering Evaluation on Real Objects
Isabella Liu · Linghao Chen · Ziyang Fu · Liwen Wu · Haian Jin · Zhong Li · Chin Ming Ryan Wong · Yi Xu · Ravi Ramamoorthi · Zexiang Xu · Hao Su
Glance and Focus: Memory Prompting for Multi-Event Video Question Answering
Ziyi Bai · Ruiping Wang · Xilin Chen
AND: Adversarial Neural Degradation for Learning Blind Image Super-Resolution
Fangzhou Luo · Xiaolin Wu · Yanhui Guo
PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile
Peiyan Dong · LEI LU · Chao Wu · Cheng Lyu · Cheng Lyu · Geng Yuan · Hao Tang · Yanzhi Wang
ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction
Jia Guo · shuai lu · Lize Jia · Weihang Zhang · Huiqi Li
NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding
Ming Hu · Lin Wang · Siyuan Yan · Don Ma · Qingli Ren · Peng Xia · Wei Feng · Peibo Duan · Lie Ju · Zongyuan Ge
Emergent Correspondence from Image Diffusion
Luming Tang · Menglin Jia · Qianqian Wang · Cheng Perng Phoo · Bharath Hariharan
OpenMask3D: Open-Vocabulary 3D Instance Segmentation
Ayca Takmaz · Elisabetta Fedele · Robert Sumner · Marc Pollefeys · Federico Tombari · Francis Engelmann
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
Kaiyu Yang · Aidan Swope · Alex Gu · Rahul Chalamala · Peiyang Song · Shixing Yu · Saad Godil · Ryan J Prenger · Animashree Anandkumar
WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data
Maurice Weber · Carlo Siebenschuh · Rory Butler · Anton Alexandrov · Valdemar Thanner · Georgios Tsolakis · Haris Jabbar · Ian Foster · Bo Li · Rick Stevens · Ce Zhang
UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
Yansong Ning · Hao Liu · Hao Wang · Zhenyu Zeng · Hui Xiong
HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection
Xingbo Du · Chonghua Wang · Ruizhe Zhong · Junchi Yan
ALGO: Synthesizing Algorithmic Programs with Generated Oracle Verifiers
Kexun Zhang · Kexun Zhang · Danqing Wang · Jingtao Xia · William Yang Wang · Lei Li
The Cambridge Law Corpus: A Corpus for Legal AI Research
Andreas Östling · Holli Sargeant · Huiyuan Xie · Ludwig Bull · Alexander Terenin · Leif Jonsson · Måns Magnusson · Felix Steffek
Metis: Understanding and Enhancing In-Network Regular Expressions
Zhengxin Zhang · Yucheng Huang · Guanglin Duan · Qing Li · Dan Zhao · Yong Jiang · Lianbo Ma · Xi Xiao · Hengyang Xu
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
Eric Nguyen · Michael Poli · Marjan Faizi · Armin Thomas · Michael Wornow · Callum Birch-Sykes · Stefano Massaroli · Aman Patel · Clayton Rabideau · Yoshua Bengio · Stefano Ermon · Christopher Ré · Stephen Baccus
ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design
Pascal Notin · Aaron Kollasch · Daniel Ritter · Lood van Niekerk · Steffanie Paul · Han Spinner · Nathan Rollins · Ada Shaw · Rose Orenbuch · Ruben Weitzman · Jonathan Frazer · Mafalda Dias · Dinko Franceschi · Yarin Gal · Debora Marks
StressID: a Multimodal Dataset for Stress Identification
Hava Chaptoukaev · Valeriya Strizhkova · Michele Panariello · Bianca Dalpaos · Aglind Reka · Valeria Manera · Susanne Thümmler · Esma ISMAILOVA · Nicholas W. · francois bremond · Massimiliano Todisco · Maria A Zuluaga · Laura M. Ferrari
VTaC: A Benchmark Dataset of Ventricular Tachycardia Alarms from ICU Monitors
Li-wei Lehman · Benjamin Moody · Harsh Deep · Feng Wu · Hasan Saeed · Lucas McCullum · Diane Perry · Tristan Struja · Qiao Li · Gari Clifford · Roger Mark
Differentiable sorting for censored time-to-event data.
Andre Vauvelle · Benjamin Wild · Roland Eils · Spiros Denaxas
Coupled Reconstruction of Cortical Surfaces by Diffeomorphic Mesh Deformation
Hao Zheng · Hongming Li · Yong Fan
Reliable Off-Policy Learning for Dosage Combinations
Jonas Schweisthal · Dennis Frauen · Valentyn Melnychuk · Stefan Feuerriegel
rPPG-Toolbox: Deep Remote PPG Toolbox
Xin Liu · Girish Narayanswamy · Akshay Paruchuri · Xiaoyu Zhang · Jiankai Tang · Yuzhe Zhang · Roni Sengupta · Shwetak Patel · Yuntao Wang · Daniel McDuff
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images
Seongsu Bae · Daeun Kyung · Jaehee Ryu · Eunbyeol Cho · Gyubok Lee · Sunjun Kweon · Jungwoo Oh · Lei Ji · Eric Chang · Tackeun Kim · Edward Choi
Unsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction
Qing Wu · Lixuan Chen · Ce Wang · Hongjiang Wei · S. Kevin Zhou · Jingyi Yu · Yuyao Zhang
RaLEs: a Benchmark for Radiology Language Evaluations
Juanma Zambrano Chaves · Nandita Bhaskhar · Maayane Attias · Jean-Benoit Delbrouck · Daniel Rubin · Andreas Loening · Curtis Langlotz · Akshay Chaudhari
Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback
Shenghuan Sun · Greg Goldgof · Atul Butte · Ahmed Alaa
Thrust: Adaptively Propels Large Language Models with External Knowledge
Xinran Zhao · Hongming Zhang · Xiaoman Pan · Wenlin Yao · Dong Yu · Jianshu Chen
How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources
Yizhong Wang · Hamish Ivison · Pradeep Dasigi · Jack Hessel · Tushar Khot · Khyathi Chandu · David Wadden · Kelsey MacMillan · Noah Smith · Iz Beltagy · Hannaneh Hajishirzi
OpenAssistant Conversations - Democratizing Large Language Model Alignment
Andreas Köpf · Yannic Kilcher · Dimitri von Rütte · Sotiris Anagnostidis · Zhi Rui Tam · Keith Stevens · Abdullah Barhoum · Duc Nguyen · Oliver Stanley · Richárd Nagyfi · Shahul ES · Sameer Suri · David Glushkov · Arnav Dantuluri · Andrew Maguire · Christoph Schuhmann · Huu Nguyen · Alexander Mattick
DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction
Mohammadreza Pourreza · Davood Rafiei
Towards Efficient Pre-Trained Language Model via Feature Correlation Distillation
Kun Huang · Xin Guo · Meng Wang
MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks
Allen Nie · Yuhui Zhang · Atharva Shailesh Amdekar · Chris Piech · Tatsunori Hashimoto · Tobias Gerstenberg
PopSign ASL v1.0: An Isolated American Sign Language Dataset Collected via Smartphones
Thad Starner · Sean Forbes · Matthew So · David Martin · Rohit Sridhar · Gururaj Deshpande · Sam Sepah · Sahir Shahryar · Khushi Bhardwaj · Tyler Kwok · Daksh Sehgal · Saad Hassan · Bill Neubauer · Sofia Vempala · Alec Tan · Jocelyn Heath · Unnathi Kumar · Priyanka Mosur · Tavenner Hall · Rajandeep Singh · Christopher Cui · Glenn Cameron · Sohier Dane · Garrett Tanzer
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
Jinhyuk Lee · Zhuyun Dai · Sai Meher Karthik Duddu · Tao Lei · Iftekhar Naim · Ming-Wei Chang · Vincent Zhao
Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Lianmin Zheng · Wei-Lin Chiang · Ying Sheng · Siyuan Zhuang · Zhanghao Wu · Yonghao Zhuang · Zi Lin · Zhuohan Li · Dacheng Li · Eric Xing · Hao Zhang · Joseph Gonzalez · Ion Stoica
Deductive Verification of Chain-of-Thought Reasoning
Zhan Ling · Yunhao Fang · Xuanlin Li · Zhiao Huang · Mingu Lee · Roland Memisevic · Hao Su
CLadder: Assessing Causal Reasoning in Language Models
Zhijing Jin · Yuen Chen · Felix Leeb · Luigi Gresele · Ojasv Kamal · Zhiheng LYU · Kevin Blin · Fernando Gonzalez Adauto · Max Kleiman-Weiner · Mrinmaya Sachan · Bernhard Schölkopf
SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agents
Shuzheng Si · Wentao Ma · Haoyu Gao · Yuchuan Wu · Ting-En Lin · Yinpei Dai · Hangyu Li · Rui Yan · Fei Huang · Yongbin Li
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
Neel Guha · Julian Nyarko · Daniel Ho · Christopher Ré · Adam Chilton · Aditya K · Alex Chohlas-Wood · Austin Peters · Brandon Waldon · Daniel Rockmore · Diego Zambrano · Dmitry Talisman · Enam Hoque · Faiz Surani · Frank Fagan · Galit Sarfaty · Gregory Dickinson · Haggai Porat · Jason Hegland · Jessica Wu · Joe Nudell · Joel Niklaus · John Nay · Jonathan Choi · Kevin Tobia · Margaret Hagan · Megan Ma · Michael Livermore · Nikon Rasumov-Rahe · Nils Holzenberger · Noam Kolt · Peter Henderson · Sean Rehaag · Sharad Goel · Shang Gao · Spencer Williams · Sunny Gandhi · Tom Zur · Varun Iyer · Zehua Li
Mathematical Capabilities of ChatGPT
Simon Frieder · Luca Pinchetti · Chevalier · Ryan-Rhys Griffiths · Tommaso Salvatori · Thomas Lukasiewicz · Philipp Petersen · Julius Berner
SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoning
Yunxiang Zhang · Xiaojun Wan
Binarized Neural Machine Translation
Yichi Zhang · Ankush Garg · Yuan Cao · Lukasz Lew · Behrooz Ghorbani · Zhiru Zhang · Orhan Firat
Don’t Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner
Zhengxiang Shi · Aldo Lipani
Unified Segment-to-Segment Framework for Simultaneous Sequence Generation
Shaolei Zhang · Yang Feng
Faith and Fate: Limits of Transformers on Compositionality
Nouha Dziri · Ximing Lu · Melanie Sclar · Xiang (Lorraine) Li · Liwei Jiang · Bill Yuchen Lin · Sean Welleck · Sean Welleck · Peter West · Chandra Bhagavatula · Ronan Le Bras · Jena Hwang · Soumya Sanyal · Xiang Ren · Allyson Ettinger · Zaid Harchaoui · Yejin Choi
Diplomat: A Dialogue Dataset for Situated PragMATic Reasoning
Hengli Li · Song-Chun Zhu · Zilong Zheng
ToolQA: A Dataset for LLM Question Answering with External Tools
Yuchen Zhuang · Yue Yu · Kuan Wang · Haotian Sun · Chao Zhang
Bayesian target optimisation for high-precision holographic optogenetics
Marcus Triplett · Marta Gajowa · Hillel Adesnik · Liam Paninski
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses
Jacob Granley · Tristan Fauvel · Matthew Chalk · Michael Beyeler
Multimodal Deep Learning Model Unveils Behavioral Dynamics of V1 Activity in Freely Moving Mice
Aiwen Xu · Yuchen Hou · Cristopher Niell · Michael Beyeler
Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system
Suhas Shrinivasan · Konstantin-Klemens Lurz · Kelli Restivo · George Denfield · Andreas Tolias · Edgar Walker · Fabian Sinz
Are Vision Transformers More Data Hungry Than Newborn Visual Systems?
Lalit Pandey · Samantha Wood · Justin Wood
Dis-inhibitory neuronal circuits can control the sign of synaptic plasticity
Julian Rossbroich · Friedemann Zenke
Learning better with Dale’s Law: A Spectral Perspective
Pingsheng Li · Jonathan Cornford · Arna Ghosh · Blake Richards
Estimating Noise Correlations Across Continuous Conditions With Wishart Processes
Amin Nejatbakhsh · Isabel Garon · Alex Williams
Data-Driven Network Neuroscience: On Data Collection and Benchmark
Jiaxing Xu · Yunhan Yang · David Huang · Sophi Shilpa Gururajapathy · Yiping Ke · Miao Qiao · Alan Wang · Haribalan Kumar · Josh McGeown · Eryn Kwon
Sequential Memory with Temporal Predictive Coding
Mufeng Tang · Helen Barron · Rafal Bogacz
Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models
Yule Wang · Zijing Wu · Chengrui Li · Anqi Wu
CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics
Fatih Dinc · Adam Shai · Mark Schnitzer · Hidenori Tanaka
Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication
Chaofei Fan · Nick Hahn · Foram Kamdar · Donald Avansino · Guy Wilson · Leigh Hochberg · Krishna V Shenoy · Jaimie Henderson · Francis Willett
Bounded rationality in structured density estimation
Tianyuan Teng · Kevin Li · Hang Zhang
SwiFT: Swin 4D fMRI Transformer
Peter Kim · Junbeom Kwon · Sunghwan Joo · Sangyoon Bae · Donggyu Lee · Yoonho Jung · Shinjae Yoo · Jiook Cha · Taesup Moon
Uncovering motifs of concurrent signaling across multiple neuronal populations
Evren Gokcen · Anna Jasper · Alison Xu · Adam Kohn · Christian Machens · Byron M Yu
Long Sequence Hopfield Memory
Hamza Chaudhry · Jacob Zavatone-Veth · Dmitry Krotov · Cengiz Pehlevan
Slow and Weak Attractor Computation Embedded in Fast and Strong E-I Balanced Neural Dynamics
Xiaohan Lin · Liyuan Li · Boxin Shi · Tiejun Huang · Yuanyuan Mi · Si Wu
Learning Topology-Agnostic EEG Representations with Geometry-Aware Modeling
Ke Yi · Yansen Wang · Kan Ren · Dongsheng Li
Scalable Transformer for PDE Surrogate Modeling
Zijie Li · Dule Shu · Amir Barati Farimani
Online PCA in Converging Self-consistent Field Equations
Xihan Li · Xiang Chen · Rasul Tutunov · Haitham Bou Ammar · Lei Wang · Jun Wang
Geometry-Informed Neural Operator for Large-Scale 3D PDEs
Zongyi Li · Nikola Kovachki · Chris Choy · Boyi Li · Jean Kossaifi · Shourya Otta · Mohammad Amin Nabian · Maximilian Stadler · Christian Hundt · Kamyar Azizzadenesheli · Animashree Anandkumar
SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics
Atul Kumar Sinha · Daniele Paliotta · Bálint Máté · John Raine · Tobias Golling · François Fleuret
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Shashank Subramanian · Peter Harrington · Kurt Keutzer · Wahid Bhimji · Dmitriy Morozov · Michael Mahoney · Amir Gholami
Equivariant flow matching
Leon Klein · Andreas Krämer · Frank Noe
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
Koen Minartz · Yoeri Poels · Simon Koop · Vlado Menkovski
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data
Wai Tong Chung · Bassem Akoush · Pushan Sharma · Alex Tamkin · Ki Sung Jung · Jacqueline Chen · Jack Guo · Davy Brouzet · Mohsen Talei · Bruno Savard · Alexei Poludnenko · Matthias Ihme
BubbleML: A Multiphase Multiphysics Dataset and Benchmarks for Machine Learning
Sheikh Md Shakeel Hassan · Arthur Feeney · Akash Dhruv · Jihoon Kim · Youngjoon Suh · Jaiyoung Ryu · Yoonjin Won · Aparna Chandramowlishwaran
SoundCam: A Dataset for Finding Humans Using Room Acoustics
Mason Wang · Samuel Clarke · Jui-Hsien Wang · Ruohan Gao · Jiajun Wu
ANTN: Bridging Autoregressive Neural Networks and Tensor Networks for Quantum Many-Body Simulation
Zhuo Chen · Laker Newhouse · Eddie Chen · Di Luo · Marin Soljacic
Newton–Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems
Lingbing Guo · Weiqing Wang · Zhuo Chen · Ningyu Zhang · Zequn Sun · Yixuan Lai · Qiang Zhang · Huajun Chen
Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
Chuanbo Hua · Federico Berto · Michael Poli · Stefano Massaroli · Jinkyoo Park
Operator Learning with Neural Fields: Tackling PDEs on General Geometries
Louis Serrano · Lise Le Boudec · Armand Kassaï Koupaï · Thomas X Wang · Yuan Yin · Jean-Noël Vittaut · Patrick Gallinari
Domain Agnostic Fourier Neural Operators
Ning Liu · Siavash Jafarzadeh · Yue Yu
Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark
Xiao-Yang Liu · Zeliang Zhang
SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models
Hongxin Li · Jingran Su · Yuntao Chen · Qing Li · ZHAO-XIANG ZHANG
Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping
Tianhao Wu · Mingdong Wu · Jiyao Zhang · Yunchong Gan · Hao Dong
What Truly Matters in Trajectory Prediction for Autonomous Driving?
Tran Phong · Haoran Wu · Cunjun Yu · Panpan Cai · Sifa Zheng · David Hsu
Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning
Yangru Huang · Peixi Peng · Yifan Zhao · Haoran Xu · Mengyue Geng · Yonghong Tian
Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
Wenlong Huang · Fei Xia · Dhruv Shah · Danny Driess · Andy Zeng · Yao Lu · Pete Florence · Igor Mordatch · Sergey Levine · Karol Hausman · brian ichter
ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling
Quanyi Li · Zhenghao (Mark) Peng · Lan Feng · Zhizheng Liu · Chenda Duan · Wenjie Mo · Bolei Zhou
Model-Based Control with Sparse Neural Dynamics
Ziang Liu · Genggeng Zhou · Jeff He · Tobia Marcucci · Fei-Fei Li · Jiajun Wu · Yunzhu Li
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
Wei Jin · Haitao Mao · Zheng Li · Haoming Jiang · Chen Luo · Hongzhi Wen · Haoyu Han · Hanqing Lu · Zhengyang Wang · Ruirui Li · Zhen Li · Monica Cheng · Rahul Goutam · Haiyang Zhang · Karthik Subbian · Suhang Wang · Yizhou Sun · Jiliang Tang · Bing Yin · Xianfeng Tang
MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection
Junho Song · Keonwoo Kim · Jeonglyul Oh · Sungzoon Cho
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting
Xu Liu · Yutong Xia · Yuxuan Liang · Junfeng Hu · Yiwei Wang · LEI BAI · Chao Huang · Zhenguang Liu · Bryan Hooi · Roger Zimmermann
CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion
Yangruibo Ding · Zijian Wang · Wasi Ahmad · Hantian Ding · Ming Tan · Nihal Jain · Murali Krishna Ramanathan · Ramesh Nallapati · Parminder Bhatia · Dan Roth · Bing Xiang
AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weeks
Chongyu Qu · Tiezheng Zhang · Hualin Qiao · jie liu · Yucheng Tang · Alan Yuille · Zongwei Zhou
Why Does Sharpness-Aware Minimization Generalize Better Than SGD?
Zixiang Chen · Junkai Zhang · Yiwen Kou · Xiangning Chen · Cho-Jui Hsieh · Quanquan Gu
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training
Aleksandra Nowak · Bram Grooten · Decebal Constantin Mocanu · Jacek Tabor
Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation
Jiawei Fan · Chao Li · Xiaolong Liu · Meina Song · Anbang Yao
Alternating Updates for Efficient Transformers
Cenk Baykal · Dylan Cutler · Nishanth Dikkala · Nikhil Ghosh · Rina Panigrahy · Xin Wang
Training Chain-of-Thought via Latent-Variable Inference
Du Phan · Matthew Douglas Hoffman · David Dohan · Sholto Douglas · Tuan Anh Le · Aaron Parisi · Pavel Sountsov · Charles Sutton · Sharad Vikram · Rif A. Saurous
Module-wise Adaptive Distillation for Multimodality Foundation Models
Chen Liang · Jiahui Yu · Ming-Hsuan Yang · Matthew Brown · Yin Cui · Tuo Zhao · Boqing Gong · Tianyi Zhou
CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models
Denis Kuznedelev · Eldar Kurtić · Elias Frantar · Dan Alistarh · Dan Alistarh
Reconciling Competing Sampling Strategies of Network Embedding
Yuchen Yan · Baoyu Jing · Lihui Liu · Ruijie Wang · Jinning Li · Tarek Abdelzaher · Hanghang Tong
Triangulation Residual Loss for Data-efficient 3D Pose Estimation
Jiachen Zhao · Tao Yu · Liang An · Yipeng Huang · Fang Deng · Qionghai Dai
SEENN: Towards Temporal Spiking Early Exit Neural Networks
Yuhang Li · Tamar Geller · Youngeun Kim · Priyadarshini Panda
Towards Unbounded Machine Unlearning
Meghdad Kurmanji · Peter Triantafillou · Jamie Hayes · Eleni Triantafillou
Deep Contract Design via Discontinuous Networks
Tonghan Wang · Paul Duetting · Dmitry Ivanov · Inbal Talgam-Cohen · David Parkes
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Zhenyu Zhang · Ying Sheng · Tianyi Zhou · Tianlong Chen · Tianlong Chen · Lianmin Zheng · Ruisi Cai · Zhao Song · Yuandong Tian · Christopher Ré · Clark Barrett · Zhangyang "Atlas" Wang · Beidi Chen
On Sparse Modern Hopfield Model
Jerry Yao-Chieh Hu · Donglin Yang · Dennis Wu · Chenwei Xu · Bo-Yu Chen · Han Liu
Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesis
Zhiyu Jin · Xuli Shen · Bin Li · Xiangyang Xue
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
Yingyi Chen · Qinghua Tao · Francesco Tonin · Johan Suykens
Validated Image Caption Rating Dataset
Lothar D Narins · Andrew Scott · Aakash Gautam · Anagha Kulkarni · Mar Castanon · Benjamin Kao · Shasta Ihorn · Yue-Ting Siu · James M. Mason · Alexander Blum · Ilmi Yoon
One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning
Zichang Liu · Zhaozhuo Xu · Benjamin Coleman · Anshumali Shrivastava
RD-Suite: A Benchmark for Ranking Distillation
Zhen Qin · Rolf Jagerman · Rama Kumar Pasumarthi · Honglei Zhuang · He Zhang · Aijun Bai · Kai Hui · Le Yan · Xuanhui Wang
Investigating how ReLU-networks encode symmetries
Georg Bökman · Fredrik Kahl
GNeSF: Generalizable Neural Semantic Fields
Hanlin Chen · Hanlin Chen · Chen Li · Mengqi Guo · Zhiwen Yan · Gim Hee Lee
GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image
Mingjian Zhu · Hanting Chen · Qiangyu YAN · Xudong Huang · Guanyu Lin · Wei Li · Zhijun Tu · Hailin Hu · Jie Hu · Yunhe Wang
Improving multimodal datasets with image captioning
Thao Nguyen · Samir Yitzhak Gadre · Gabriel Ilharco · Sewoong Oh · Ludwig Schmidt
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology
Marco Aversa · Gabriel Nobis · Miriam Hägele · Kai Standvoss · Mihaela Chirica · Roderick Murray-Smith · Ahmed Alaa · Lukas Ruff · Daniela Ivanova · Wojciech Samek · Frederick Klauschen · Bruno Sanguinetti · Luis Oala
Continuous-Time Functional Diffusion Processes
Giulio Franzese · Giulio Corallo · Simone Rossi · Markus Heinonen · Maurizio Filippone · Pietro Michiardi
DreamWaltz: Make a Scene with Complex 3D Animatable Avatars
Yukun Huang · Jianan Wang · Ailing Zeng · He CAO · Xianbiao Qi · Yukai Shi · Zheng-Jun Zha · Lei Zhang
Rethinking Conditional Diffusion Sampling with Progressive Guidance
Anh-Dung Dinh · Daochang Liu · Chang Xu
Add and Thin: Diffusion for Temporal Point Processes
David Lüdke · Marin Biloš · Oleksandr Shchur · Marten Lienen · Stephan Günnemann
Improving Diffusion-Based Image Synthesis with Context Prediction
Ling Yang · Jingwei Liu · Shenda Hong · Zhilong Zhang · Zhilin Huang · Zheming Cai · Wentao Zhang · Bin CUI
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
Haotian Xue · Alexandre Araujo · Bin Hu · Yongxin Chen
Beta Diffusion
Mingyuan Zhou · Tianqi Chen · Zhendong Wang · Huangjie Zheng
Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows
Alexandre Verine · Benjamin Negrevergne · Muni Sreenivas Pydi · Yann Chevaleyre
Concept Algebra for (Score-Based) Text-Controlled Generative Models
Zihao Wang · Lin Gui · Jeffrey Negrea · Victor Veitch
On the Generalization Properties of Diffusion Models
Puheng Li · Zhong Li · Huishuai Zhang · Jiang Bian
Arbitrarily Scalable Environment Generators via Neural Cellular Automata
Yulun Zhang · Matthew Fontaine · Varun Bhatt · Stefanos Nikolaidis · Jiaoyang Li
UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models
Wenliang Zhao · Lujia Bai · Yongming Rao · Jie Zhou · Jiwen Lu
Temporal Dynamic Quantization for Diffusion Models
Junhyuk So · Jungwon Lee · Daehyun Ahn · Hyungjun Kim · Eunhyeok Park
Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment
Hao Liu · Wilson Yan · Pieter Abbeel
Joint Prompt Optimization of Stacked LLMs using Variational Inference
Alessandro Sordoni · Eric Yuan · Marc-Alexandre Côté · Matheus Pereira · Adam Trischler · Ziang Xiao · Arian Hosseini · Friederike Niedtner · Nicolas Le Roux
Expanding Small-Scale Datasets with Guided Imagination
Yifan Zhang · Daquan Zhou · Bryan Hooi · Kai Wang · Jiashi Feng
Inserting Anybody in Diffusion Models via Celeb Basis
Ge Yuan · Xiaodong Cun · Yong Zhang · Maomao Li · Chenyang Qi · Xintao Wang · Ying Shan · Huicheng Zheng
Customizable Image Synthesis with Multiple Subjects
Zhiheng Liu · Yifei Zhang · Yujun Shen · Kecheng Zheng · Kai Zhu · Ruili Feng · Yu Liu · Deli Zhao · Jingren Zhou · Yang Cao
Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models
Shihao Zhao · Dongdong Chen · Yen-Chun Chen · Jianmin Bao · Shaozhe Hao · Lu Yuan · Kwan-Yee K. Wong
GlyphControl: Glyph Conditional Control for Visual Text Generation
Yukang Yang · Dongnan Gui · YUHUI YUAN · Weicong Liang · Haisong Ding · Han Hu · Kai Chen
Score-based Data Assimilation
François Rozet · Gilles Louppe
Diffusion Probabilistic Models for Structured Node Classification
Hyosoon Jang · Seonghyun Park · Sangwoo Mo · Sungsoo Ahn
Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
TaeHo Yoon · Kibeom Myoung · Keon Lee · Jaewoong Cho · Albert No · Ernest Ryu
Semi-Implicit Denoising Diffusion Models (SIDDMs)
yanwu xu · Mingming Gong · Shaoan Xie · Wei Wei · Matthias Grundmann · Kayhan Batmanghelich · Tingbo Hou
Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions
Dongjie Wang · Meng Xiao · Min Wu · pengfei wang · Yuanchun Zhou · Yanjie Fu
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder
Michael Bereket · Theofanis Karaletsos
Constructing Non-isotropic Gaussian Diffusion Model Using Isotropic Gaussian Diffusion Model for Image Editing
Xi Yu · Xiang Gu · Haozhi Liu · Jian Sun
Synthcity: a benchmark framework for diverse use cases of tabular synthetic data
Zhaozhi Qian · Rob Davis · Mihaela van der Schaar
Euler-Lagrange Analysis of Generative Adversarial Networks
Siddarth Asokan · Chandra Seelamantula
Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics
Liming Wu · Zhichao Hou · Jirui Yuan · Yu Rong · Wenbing Huang
Efficient Learning of Linear Graph Neural Networks via Node Subsampling
Seiyun Shin · Ilan Shomorony · Han Zhao
A Comprehensive Study on Text-attributed Graphs: Benchmarking and Rethinking
Hao Yan · Chaozhuo Li · Ruosong Long · Chao Yan · Jianan Zhao · Wenwen Zhuang · Jun Yin · Peiyan Zhang · Weihao Han · Hao Sun · Weiwei Deng · Qi Zhang · Lichao Sun · Xing Xie · Senzhang Wang
Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
Oleg Platonov · Denis Kuznedelev · Artem Babenko · Liudmila Prokhorenkova
CAT-Walk: Inductive Hypergraph Learning via Set Walks
Ali Behrouz · Farnoosh Hashemi · Sadaf Sadeghian · Margo Seltzer
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs
Mangpo Phothilimthana · Sami Abu-El-Haija · Kaidi Cao · Bahare Fatemi · Michael Burrows · Charith Mendis · Bryan Perozzi
A Theory of Link Prediction via Relational Weisfeiler-Leman on Knowledge Graphs
Xingyue Huang · Miguel Romero · Ismail Ceylan · Pablo Barceló
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
Shenyang Huang · Farimah Poursafaei · Jacob Danovitch · Matthias Fey · Weihua Hu · Emanuele Rossi · Jure Leskovec · Michael Bronstein · Guillaume Rabusseau · Reihaneh Rabbany
Fine-grained Expressivity of Graph Neural Networks
Jan Böker · Ron Levie · Ningyuan Huang · Soledad Villar · Christopher Morris
Approximately Equivariant Graph Networks
Ningyuan Huang · Ron Levie · Soledad Villar
TopoSRL: Topology preserving self-supervised Simplicial Representation Learning
Hiren Madhu · Sundeep Prabhakar Chepuri
Lovász Principle for Unsupervised Graph Representation Learning
Ziheng Sun · Chris Ding · Jicong Fan
Demystifying Oversmoothing in Attention-Based Graph Neural Networks
Xinyi Wu · Amir Ajorlou · Zihui Wu · Ali Jadbabaie
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
Lukas Gosch · Simon Geisler · Daniel Sturm · Bertrand Charpentier · Daniel Zügner · Stephan Günnemann
WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding
Yanchao Tan · Zihao Zhou · Hang Lv · Weiming Liu · Carl Yang
Are GATs Out of Balance?
Nimrah Mustafa · Aleksandar Bojchevski · Rebekka Burkholz
PRODIGY: Enabling In-context Learning Over Graphs
Qian Huang · Hongyu Ren · Peng Chen · Gregor Kržmanc · Daniel Zeng · Percy Liang · Jure Leskovec
GSLB: The Graph Structure Learning Benchmark
Zhixun Li · Liang Wang · Xin Sun · Yifan Luo · Yanqiao Zhu · Dingshuo Chen · Yingtao Luo · Xiangxin Zhou · Qiang Liu · Shu Wu · Liang Wang · Jeffrey Yu
ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training
Antonio Norelli · Marco Fumero · Valentino Maiorca · Luca Moschella · Emanuele Rodolà · Francesco Locatello
Kissing to Find a Match: Efficient Low-Rank Permutation Representation
Hannah Dröge · Zorah Lähner · Yuval Bahat · Onofre Martorell Nadal · Felix Heide · Michael Moeller
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
Tom Hartvigsen · Swami Sankaranarayanan · Hamid Palangi · Yoon Kim · Marzyeh Ghassemi
Analyzing Vision Transformers for Image Classification in Class Embedding Space
Martina G. Vilas · Timothy Schaumlöffel · Gemma Roig
Topology-Aware Uncertainty for Image Segmentation
Saumya Gupta · Yikai Zhang · Xiaoling Hu · Prateek Prasanna · Chao Chen
Learning Adaptive Tensorial Density Fields for Clean Cryo-ET Reconstruction
YUANHAO WANG · Ramzi Idoughi · Wolfgang Heidrich
Task-aware Distributed Source Coding under Dynamic Bandwidth
Po-han Li · Sravan Kumar Ankireddy · Ruihan (Philip) Zhao · Hossein Nourkhiz Mahjoub · Ehsan Moradi Pari · Ufuk Topcu · Sandeep Chinchali · Hyeji Kim
An Inverse Scaling Law for CLIP Training
Xianhang Li · Zeyu Wang · Cihang Xie
Online learning of long-range dependencies
Nicolas Zucchet · Robert Meier · Simon Schug · Asier Mujika · Joao Sacramento
Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations
Hyeonjeong Ha · Minseon Kim · Sung Ju Hwang
Improving Adversarial Robustness via Information Bottleneck Distillation
Huafeng Kuang · Hong Liu · Yongjian Wu · Shin'ichi Satoh · Rongrong Ji
Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
Naman Deep Singh · Francesco Croce · Matthias Hein
Cola: A Benchmark for Compositional Text-to-image Retrieval
Arijit Ray · Filip Radenovic · Abhimanyu Dubey · Bryan Plummer · Ranjay Krishna · Kate Saenko
Holistic Transfer: Towards Non-Disruptive Fine-Tuning with Partial Target Data
Cheng-Hao Tu · Hong-You Chen · Zheda Mai · Jike Zhong · Vardaan Pahuja · Tanya Berger-Wolf · Song Gao · Charles Stewart · Yu Su · Wei-Lun (Harry) Chao
Towards Last-layer Retraining for Group Robustness with Fewer Annotations
Tyler LaBonte · Vidya Muthukumar · Abhishek Kumar
Don’t blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy
Aahlad Manas Puli · Lily Zhang · Yoav Wald · Rajesh Ranganath
Blurred-Dilated Method for Adversarial Attacks
Yang Deng · Weibin Wu · Jianping Zhang · Zibin Zheng
RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions
Lingdong Kong · Shaoyuan Xie · Hanjiang Hu · Lai Xing Ng · Benoit Cottereau · Wei Tsang Ooi
Asymmetric Certified Robustness via Feature-Convex Neural Networks
Samuel Pfrommer · Brendon Anderson · Julien Piet · Somayeh Sojoudi
AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
Yang Yu · Qi Liu · Kai Zhang · Yuren Zhang · Chao Song · Min Hou · Yuqing Yuan · Zhihao Ye · ZAIXI ZHANG · Sanshi Lei Yu
HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception
Junkun Yuan · Xinyu Zhang · Hao Zhou · Jian Wang · Zhongwei Qiu · Zhiyin Shao · Shaofeng Zhang · Sifan Long · Kun Kuang · Kun Yao · Junyu Han · Errui Ding · Lanfen Lin · Fei Wu · Jingdong Wang
Implicit Contrastive Representation Learning with Guided Stop-gradient
Byeongchan Lee · Sehyun Lee
[Re] Masked Autoencoders Are Small Scale Vision Learners: A Reproduction Under Resource Constraints
Athanasios Charisoudis · Simon Ekman von Huth · Emil Jansson
Reverse Engineering Self-Supervised Learning
Ido Ben-Shaul · Ravid Shwartz-Ziv · Tomer Galanti · Shai Dekel · Yann LeCun
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
Alex Tamkin · Margalit Glasgow · Xiluo He · Noah Goodman
Towards In-context Scene Understanding
Ivana Balazevic · David Steiner · Nikhil Parthasarathy · Relja Arandjelović · Olivier Henaff
Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training
Jian Meng · Li Yang · Kyungmin Lee · Jinwoo Shin · Deliang Fan · Jae-sun Seo
SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
Adam Stewart · Nils Lehmann · Isaac Corley · Yi Wang · Yi-Chia Chang · Nassim Ait Ait Ali Braham · Shradha Sehgal · Caleb Robinson · Arindam Banerjee
Taming Local Effects in Graph-based Spatiotemporal Forecasting
Andrea Cini · Ivan Marisca · Daniele Zambon · Cesare Alippi
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
Alistair White · Niki Kilbertus · Maximilian Gelbrecht · Niklas Boers
Automatic Integration for Spatiotemporal Neural Point Processes
Zihao Zhou · Rose Yu
Transformers learn through gradual rank increase
Enric Boix-Adsera · Etai Littwin · Emmanuel Abbe · Samy Bengio · Joshua Susskind
On the Power of SVD in the Stochastic Block Model
Xinyu Mao · Jiapeng Zhang
Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration
Parikshit Gopalan · Michael Kim · Omer Reingold
Precise asymptotic generalization for multiclass classification with overparameterized linear models
David Wu · Anant Sahai
Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets
Arthur da Cunha · Arthur da Cunha · Francesco D'Amore · Natale
Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability
Jingfeng Wu · Vladimir Braverman · Jason Lee
Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks
Zihao Wang · Lei Wu
Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign?
Erin George · Michael Murray · William Swartworth · Deanna Needell
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks
Eshaan Nichani · Alex Damian · Jason Lee
The Crucial Role of Normalization in Sharpness-Aware Minimization
Yan Dai · Kwangjun Ahn · Suvrit Sra
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces
Odelia Melamed · Gilad Yehudai · Gal Vardi
Abide by the law and follow the flow: conservation laws for gradient flows
Sibylle Marcotte · Remi Gribonval · Gabriel Peyré
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory
Sokhna Diarra Mbacke · Florence Clerc · Pascal Germain
On skip connections and normalisation layers in deep optimisation
Lachlan MacDonald · Jack Valmadre · Hemanth Saratchandran · Simon Lucey
Provable Guarantees for Neural Networks via Gradient Feature Learning
Zhenmei Shi · Junyi Wei · Yingyu Liang
Small Transformers Compute Universal Metric Embeddings
Anastasis Kratsios · Valentin Debarnot · Ivan Dokmanić
Learning DAGs from Data with Few Root Causes
Panagiotis Misiakos · Chris Wendler · Markus Püschel
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
Valentyn Melnychuk · Dennis Frauen · Stefan Feuerriegel
Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data
Saptarshi Roy · Raymond K. W. Wong · Yang Ni
CLIP-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments
Jessica Dai · Paula Gradu · Christopher Harshaw
Cause-Effect Inference in Location-Scale Noise Models: Maximum Likelihood vs. Independence Testing
Xiangyu Sun · Oliver Schulte
Analysis of Variance of Multiple Causal Networks
Zhongli Jiang · Dabao Zhang
Intervention Generalization: A View from Factor Graph Models
Gecia Bravo-Hermsdorff · David Watson · Jialin Yu · Jakob Zeitler · Ricardo Silva
Conditional independence testing under misspecified inductive biases
Felipe Maia Polo · Yuekai Sun · Moulinath Banerjee
DataPerf: Benchmarks for Data-Centric AI Development
Mark Mazumder · Colby Banbury · Xiaozhe Yao · Bojan Karlaš · William Gaviria Rojas · Sudnya Diamos · Greg Diamos · Lynn He · Alicia Parrish · Hannah Rose Kirk · Jessica Quaye · Charvi Rastogi · Douwe Kiela · David Jurado · David Kanter · Rafael Mosquera · Will Cukierski · Juan Ciro · Lora Aroyo · Bilge Acun · Lingjiao Chen · Mehul Raje · Max Bartolo · Evan Sabri Eyuboglu · Amirata Ghorbani · Emmett Goodman · Addison Howard · Oana Inel · Tariq Kane · Christine R. Kirkpatrick · D. Sculley · Tzu-Sheng Kuo · Jonas Mueller · Tristan Thrush · Joaquin Vanschoren · Margaret Warren · Adina Williams · Serena Yeung · Newsha Ardalani · Praveen Paritosh · Ce Zhang · James Zou · Carole-Jean Wu · Cody Coleman · Andrew Ng · Peter Mattson · Vijay Janapa Reddi
PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning.
Mingjia Shi · Yuhao Zhou · Kai Wang · Huaizheng Zhang · Shudong Huang · Qing Ye · Jiancheng Lv
Markovian Sliced Wasserstein Distances: Beyond Independent Projections
Khai Nguyen · Tongzheng Ren · Nhat Ho
Interaction Measures, Partition Lattices and Kernel Tests for High-Order Interactions
Zhaolu Liu · Robert Peach · Pedro A.M Mediano · Mauricio Barahona
Koopman Kernel Regression
Petar Bevanda · Max Beier · Armin Lederer · Stefan Sosnowski · Eyke Hüllermeier · Sandra Hirche
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift
Xingdong Feng · Xin HE · Caixing Wang · Chao Wang · Jingnan Zhang
Sharp Spectral Rates for Koopman Operator Learning
Vladimir Kostic · Karim Lounici · Pietro Novelli · Massimiliano Pontil
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization
Clement Benard · Brian Staber · Sébastien Da Veiga
Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms
Tiancheng Jin · Junyan Liu · Haipeng Luo
Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks
Alexander Modell · Ian Gallagher · Emma Ceccherini · Nick Whiteley · Patrick Rubin-Delanchy
Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
Shashanka Venkataramanan · Ewa Kijak · laurent amsaleg · Yannis Avrithis
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities
Hugues Van Assel · Titouan Vayer · Rémi Flamary · Nicolas Courty
MAViL: Masked Audio-Video Learners
Po-Yao Huang · Vasu Sharma · Hu Xu · Chaitanya Ryali · Chaitanya Ryali · haoqi fan · Yanghao Li · Shang-Wen Li · Gargi Ghosh · Jitendra Malik · Christoph Feichtenhofer
Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs
CHEN SHENGYUAN · Yunfeng Cai · Huang Fang · Xiao Huang · Mingming Sun
Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks
Haoyi Duan · Yan Xia · Zhou Mingze · Li Tang · Jieming Zhu · Zhou Zhao
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective
João Carvalho · Mengtao Zhang · Robin Geyer · Carlos Cotrini · Joachim M Buhmann
DynaDojo: An Extensible Platform for Benchmarking Scaling in Dynamical System Identification
Logan M Bhamidipaty · Tommy Bruzzese · Caryn Tran · Rami Ratl Mrad · Maxinder S. Kanwal
When Does Confidence-Based Cascade Deferral Suffice?
Wittawat Jitkrittum · Neha Gupta · Aditya Menon · Harikrishna Narasimhan · Ankit Rawat · Sanjiv Kumar
Learning Curves for Deep Structured Gaussian Feature Models
Jacob Zavatone-Veth · Cengiz Pehlevan
Scalarization for Multi-Task and Multi-Domain Learning at Scale
Amelie Royer · Tijmen Blankevoort · Babak Ehteshami Bejnordi
What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation
Benedikt Blumenstiel · Johannes Jakubik · Hilde Kuehne · Michael Vössing
Optimal testing using combined test statistics across independent studies
Lasse Vuursteen · Botond Szabo · Aad van der Vaart · Harry van Zanten
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning
Dami Choi · Derrick Xin · Hamid Dadkhahi · Justin Gilmer · Ankush Garg · Orhan Firat · Chih-Kuan Yeh · Andrew Dai · Behrooz Ghorbani
Language Semantic Graph Guided Data-Efficient Learning
Wenxuan Ma · Shuang Li · lincan Cai · Jingxuan Kang
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
Ildus Sadrtdinov · Dmitrii Pozdeev · Dmitry Vetrov · Ekaterina Lobacheva
FedL2P: Federated Learning to Personalize
Royson Lee · Minyoung Kim · Da Li · Xinchi Qiu · Timothy Hospedales · Ferenc Huszar · Nicholas Lane
Adaptive Test-Time Personalization for Federated Learning
Wenxuan Bao · Tianxin Wei · Haohan Wang · Jingrui He
Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
Dapeng Hu · Jian Liang · Jun Hao Liew · Chuhui Xue · Song Bai · Xinchao Wang
ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
Junguang Jiang · Baixu Chen · Junwei Pan · Ximei Wang · Dapeng Liu · Jie Jiang · Mingsheng Long
Zero-Shot Anomaly Detection via Batch Normalization
Aodong Li · Chen Qiu · Marius Kloft · Padhraic Smyth · Maja Rudolph · Stephan Mandt
Efficient Policy Adaptation with Contrastive Prompt Ensemble for Embodied Agents
wonje choi · Woo Kyung Kim · SeungHyun Kim · Honguk Woo
FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning
Zhuo Huang · Li Shen · Jun Yu · Bo Han · Tongliang Liu
Orthogonal Non-negative Tensor Factorization based Multi-view Clustering
Jing Li · Quanxue Gao · QIANQIAN WANG · Ming Yang · Wei Xia
SwapPrompt: Test-Time Prompt Adaptation for Vision-Language Models
XIAOSONG MA · Jie ZHANG · Song Guo · Wenchao Xu
Large sample spectral analysis of graph-based multi-manifold clustering
Nicolas Garcia Trillos · Pengfei He · Chenghui Li
Multi-Swap k-Means++
Lorenzo Beretta · Vincent Cohen-Addad · Silvio Lattanzi · Nikos Parotsidis
Semi-Supervised Domain Generalization with Known and Unknown Classes
Lei Zhang · Ji-Fu Li · Wei Wang
Harnessing Hard Mixed Samples with Decoupled Regularizer
Zicheng Liu · Siyuan Li · Ge Wang · Lirong Wu · Cheng Tan · Stan Z. Li
Binary Classification with Confidence Difference
Wei Wang · Lei Feng · Yuchen Jiang · Gang Niu · Min-Ling Zhang · Masashi Sugiyama
Path following algorithms for $\ell_2$-regularized $M$-estimation with approximation guarantee
Yunzhang Zhu · Renxiong Liu
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity
Youssef Allouah · Rachid Guerraoui · Nirupam Gupta · Rafael Pinot · Rafael Pinot · Geovani Rizk
Neural Fields with Hard Constraints of Arbitrary Differential Order
Fangcheng Zhong · Kyle Fogarty · Param Hanji · Tianhao Wu · Alejandro Sztrajman · Andrew Spielberg · Andrea Tagliasacchi · Petra Bosilj · Cengiz Oztireli
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms
Lam Nguyen · Trang H. Tran
Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem
Jincheng Cao · Ruichen Jiang · Nazanin Abolfazli · Erfan Yazdandoost Hamedani · Aryan Mokhtari
Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization
Yuyang Qiu · Uday Shanbhag · Farzad Yousefian
Non-Convex Bilevel Optimization with Time-Varying Objective Functions
Sen Lin · Daouda Sow · Kaiyi Ji · Yingbin Liang · Ness Shroff
Distributionally Robust Linear Quadratic Control
Bahar Taskesen · Dan Iancu · Çağıl Koçyiğit · Daniel Kuhn
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
Sihan Zeng · Thinh Doan · Justin Romberg
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities
Aleksandr Beznosikov · Martin Takac · Alexander Gasnikov
Boosting with Tempered Exponential Measures
Richard Nock · Ehsan Amid · Manfred Warmuth
Computational Guarantees for Doubly Entropic Wasserstein Barycenters
Tomas Vaskevicius · Lénaïc Chizat
A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
Kansei Ushiyama · Shun Sato · Takayasu Matsuo
Optimizing over trained GNNs via symmetry breaking
Shiqiang Zhang · Juan Campos · Christian Feldmann · David Walz · Frederik Sandfort · Miriam Mathea · Calvin Tsay · Ruth Misener
Advancing Bayesian Optimization via Learning Correlated Latent Space
Seunghun Lee · Jaewon Chu · Sihyeon Kim · Juyeon Ko · Hyunwoo Kim
Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick
Lennert De Smet · Emanuele Sansone · Pedro Zuidberg Dos Martires
DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
Ahmed Khaled · Konstantin Mishchenko · Chi Jin
GloptiNets: Scalable Non-Convex Optimization with Certificates
Gaspard Beugnot · Julien Mairal · Alessandro Rudi
Globally solving the Gromov-Wasserstein problem for point clouds in low dimensional Euclidean spaces
Martin Ryner · Jan Kronqvist · Johan Karlsson
Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence
Marie Maros · Gesualdo Scutari
Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt
Yining Ma · Zhiguang Cao · Yeow Meng Chee
Robust Learning for Smoothed Online Convex Optimization with Feedback Delay
Pengfei Li · Jianyi Yang · Adam Wierman · Shaolei Ren
Exponentially Convergent Algorithms for Supervised Matrix Factorization
Joowon Lee · Hanbaek Lyu · Weixin Yao
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems
Anh Viet Do · Aneta Neumann · Frank Neumann · Andrew Sutton
(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
Mathieu Even · Scott Pesme · Suriya Gunasekar · Nicolas Flammarion
Stable Nonconvex-Nonconcave Training via Linear Interpolation
Thomas Pethick · Wanyun Xie · Volkan Cevher
Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization
Yankun Huang · Qihang Lin
LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees
Shangyuan LIU · Linglingzhi Zhu · Anthony Man-Cho So
Weitzman's Rule for Pandora's Box with Correlations
Evangelia Gergatsouli · Christos Tzamos
A Unified Approach for Maximizing Continuous DR-submodular Functions
Mohammad Pedramfar · Christopher Quinn · Vaneet Aggarwal
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
Anastasiia Koloskova · Ryan McKenna · Zachary Charles · John Rush · H. Brendan McMahan
Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure
Angela Yuan · Chris Junchi Li · Gauthier Gidel · Michael Jordan · Quanquan Gu · Simon Du
A Guide Through the Zoo of Biased SGD
Yury Demidovich · Grigory Malinovsky · Igor Sokolov · Peter Richtarik
Failure-Aware Gaussian Process Optimization with Regret Bounds
Shogo Iwazaki · Shion Takeno · Tomohiko Tanabe · Mitsuru Irie
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization
Kamil Dreczkowski · Antoine Grosnit · Haitham Bou Ammar
Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
Nikita Kornilov · Ohad Shamir · Aleksandr Lobanov · Darina Dvinskikh · Alexander Gasnikov · Innokentiy Shibaev · Eduard Gorbunov · Samuel Horváth
Bayesian Optimization with Cost-varying Variable Subsets
Sebastian Tay · Chuan Sheng Foo · Daisuke Urano · Richalynn Leong · Bryan Kian Hsiang Low
Self-Correcting Bayesian Optimization through Bayesian Active Learning
Carl Hvarfner · Erik Hellsten · Frank Hutter · Luigi Nardi
How to Turn Your Knowledge Graph Embeddings into Generative Models
Lorenzo Loconte · Nicola Di Mauro · Robert Peharz · Antonio Vergari
Moment Matching Denoising Gibbs Sampling
Mingtian Zhang · Alex Hawkins-Hooker · Brooks Paige · David Barber
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference
Julia Linhart · Alexandre Gramfort · Pedro Rodrigues
Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
Van Cuong Pham · Cuong C Nguyen · Cuong Nguyen · Trung Le · Dinh Phung · Gustavo Carneiro · Thanh-Toan Do
Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach
Fabian Zaiser · Andrzej Murawski · Chih-Hao Luke Ong
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration
Longlin Yu · Tianyu Xie · Yu Zhu · Tong Yang · Xiangyu Zhang · Cheng Zhang
Quantification of Uncertainty with Adversarial Models
Kajetan Schweighofer · Lukas Aichberger · Mykyta Ielanskyi · Günter Klambauer · Sepp Hochreiter
Collapsed Inference for Bayesian Deep Learning
Zhe Zeng · Guy Van den Broeck
Function Space Bayesian Pseudocoreset for Bayesian Neural Networks
Balhae Kim · Hyungi Lee · Juho Lee
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks
Steven Adriaensen · Herilalaina Rakotoarison · Samuel Müller · Frank Hutter
Energy-Based Sliced Wasserstein Distance
Khai Nguyen · Nhat Ho
On the Identifiability and Interpretability of Gaussian Process Models
Jiawen Chen · Wancen Mu · Yun Li · Didong Li
Probabilistic Exponential Integrators
Nathanael Bosch · Philipp Hennig · Filip Tronarp
Approximate inference of marginals using the IBIA framework
Shivani Bathla · Vinita Vasudevan
Characteristic Circuits
Zhongjie Yu · Martin Trapp · Kristian Kersting
Discriminative Calibration: Check Bayesian Computation from Simulations and Flexible Classifier
Yuling Yao · Justin Domke
Learning Rate Free Sampling in Constrained Domains
Louis Sharrock · Lester Mackey · Christopher Nemeth
Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions
Xiang Cheng · Bohan Wang · Jingzhao Zhang · Yusong Zhu
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond
Omar Chehab · Aapo Hyvarinen · Andrej Risteski
Structure Learning with Adaptive Random Neighborhood Informed MCMC
Xitong Liang · Alberto Caron · Samuel Livingstone · Jim Griffin
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
Tristan Deleu · Mizu Nishikawa-Toomey · Jithendaraa Subramanian · Nikolay Malkin · Laurent Charlin · Yoshua Bengio
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs
Kevin Course · Prasanth Nair
KuaiSim: A Comprehensive Simulator for Recommender Systems
Kesen Zhao · Shuchang Liu · Qingpeng Cai · Xiangyu Zhao · Ziru Liu · Dong Zheng · Peng Jiang · Kun Gai
Behavior Alignment via Reward Function Optimization
Dhawal Gupta · Yash Chandak · Scott Jordan · Philip Thomas · Bruno C. da Silva
Online Nonstochastic Model-Free Reinforcement Learning
Udaya Ghai · Arushi Gupta · Wenhan Xia · Karan Singh · Elad Hazan
Supervised Pretraining Can Learn In-Context Reinforcement Learning
Jonathan Lee · Annie Xie · Aldo Pacchiano · Yash Chandak · Chelsea Finn · Ofir Nachum · Emma Brunskill
Learning World Models with Identifiable Factorization
Yuren Liu · Biwei Huang · Zhengmao Zhu · Honglong Tian · Mingming Gong · Yang Yu · Kun Zhang
Facing Off World Model Backbones: RNNs, Transformers, and S4
Fei Deng · Junyeong Park · Sungjin Ahn
Imitation Learning from Imperfection: Theoretical Justifications and Algorithms
Ziniu Li · Tian Xu · Zeyu Qin · Yang Yu · Zhi-Quan Luo
Policy Optimization for Continuous Reinforcement Learning
HANYANG ZHAO · Wenpin Tang · David Yao
Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation
GUOJUN XIONG · Jian Li
Offline Reinforcement Learning with Differential Privacy
Dan Qiao · Yu-Xiang Wang
SustainGym: Reinforcement Learning Environments for Sustainable Energy Systems
Christopher Yeh · Victor Li · Rajeev Datta · Julio Arroyo · Nicolas Christianson · Chi Zhang · Yize Chen · Mohammad Mehdi Hosseini · Azarang Golmohammadi · Yuanyuan Shi · Yisong Yue · Adam Wierman
When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning
Siliang Zeng · Chenliang Li · Alfredo Garcia · Mingyi Hong
Model-Free Active Exploration in Reinforcement Learning
Alessio Russo · Alessio Russo · Alexandre Proutiere
Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals
Yue Wu · Yewen Fan · Paul Pu Liang · Amos Azaria · Yuanzhi Li · Tom Mitchell
Probabilistic Inference in Reinforcement Learning Done Right
Jean Tarbouriech · Tor Lattimore · Brendan O'Donoghue
Learning Generalizable Agents via Saliency-guided Features Decorrelation
Sili Huang · Yanchao Sun · Jifeng Hu · Siyuan Guo · Hechang Chen · Yi Chang · Lichao Sun · Bo Yang
Accelerating Exploration with Unlabeled Prior Data
Qiyang Li · Jason Zhang · Dibya Ghosh · Amy Zhang · Sergey Levine
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates
Guangchen Lan · Han Wang · James Anderson · Christopher Brinton · Vaneet Aggarwal
Provably Efficient Offline Reinforcement Learning in Regular Decision Processes
Roberto Cipollone · Anders Jonsson · Alessandro Ronca · Mohammad Sadegh Talebi
Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
Hao Sun · Alihan Hüyük · Daniel Jarrett · Mihaela van der Schaar
Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization
Xiangsen Wang · Haoran Xu · Yinan Zheng · Xianyuan Zhan
Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
Shenzhi Wang · Qisen Yang · Jiawei Gao · Matthieu Lin · HAO CHEN · Liwei Wu · Ning Jia · Shiji Song · Gao Huang
Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans
Kyowoon Lee · Seongun Kim · Jaesik Choi
Offline Imitation Learning with Variational Counterfactual Reasoning
Zexu Sun · Bowei He · Jinxin Liu · Xu Chen · Chen Ma · Shuai Zhang
ODE-based Recurrent Model-free Reinforcement Learning for POMDPs
Xuanle Zhao · Duzhen Zhang · Han Liyuan · Tielin Zhang · Bo Xu
Reinforcement Learning with Fast and Forgetful Memory
Steven Morad · Ryan Kortvelesy · Stephan Liwicki · Amanda Prorok
COOM: A Game Benchmark for Continual Reinforcement Learning
Tristan Tomilin · Meng Fang · Yudi Zhang · Mykola Pechenizkiy
LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
Bo Liu · Yifeng Zhu · Chongkai Gao · Yihao Feng · Qiang Liu · Yuke Zhu · Peter Stone
Guide Your Agent with Adaptive Multimodal Rewards
Changyeon Kim · Younggyo Seo · Hao Liu · Lisa Lee · Jinwoo Shin · Honglak Lee · Kimin Lee
Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
Siming Lan · Rui Zhang · Qi Yi · Jiaming Guo · Shaohui Peng · Yunkai Gao · Fan Wu · Ruizhi Chen · Zidong Du · Xing Hu · xishan zhang · Ling Li · Yunji Chen
Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies
Michael Beukman · Devon Jarvis · Richard Klein · Steven James · Benjamin Rosman
LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios
Yazhe Niu · YUAN PU · Zhenjie Yang · Xueyan Li · Tong Zhou · Jiyuan Ren · Shuai Hu · Hongsheng Li · Yu Liu
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration
Shuai Zhang · Hongkang Li · Meng Wang · Miao Liu · Pin-Yu Chen · Songtao Lu · Songtao Lu · Sijia Liu · Keerthiram Murugesan · Subhajit Chaudhury
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards
Alexandre Rame · Guillaume Couairon · Corentin Dancette · Jean-Baptiste Gaya · Mustafa Shukor · Laure Soulier · Matthieu Cord
Learning from Visual Observation via Offline Pretrained State-to-Go Transformer
Bohan Zhou · Ke Li · Jiechuan Jiang · Zongqing Lu
Learning from Active Human Involvement through Proxy Value Propagation
Zhenghao (Mark) Peng · Wenjie Mo · Chenda Duan · Quanyi Li · Bolei Zhou
Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
Nate Rahn · Pierluca D'Oro · Harley Wiltzer · Pierre-Luc Bacon · Marc Bellemare
MIMEx: Intrinsic Rewards from Masked Input Modeling
Toru Lin · Allan Jabri
Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach
Yudi Zhang · Yali Du · Biwei Huang · Ziyan Wang · Jun Wang · Meng Fang · Mykola Pechenizkiy
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
Sattar Vakili · Julia Olkhovskaya
Ordering-based Conditions for Global Convergence of Policy Gradient Methods
Jincheng Mei · Bo Dai · Alekh Agarwal · Mohammad Ghavamzadeh · Csaba Szepesvari · Dale Schuurmans
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
Kaiwen Wang · Kevin Zhou · Runzhe Wu · Nathan Kallus · Wen Sun
Learning Shared Safety Constraints from Multi-task Demonstrations
Konwoo Kim · Gokul Swamy · ZUXIN LIU · DING ZHAO · Sanjiban Choudhury · Steven Wu
Conservative Offline Policy Adaptation in Multi-Agent Games
Chengjie Wu · Pingzhong Tang · Jun Yang · Yujing Hu · Tangjie Lv · Changjie Fan · Chongjie Zhang
Policy Space Diversity for Non-Transitive Games
Jian Yao · Weiming Liu · Haobo Fu · Yaodong Yang · Stephen McAleer · Qiang Fu · Wei Yang
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL
Pascal Leroy · Pablo G. Morato · Jonathan Pisane · Athanasios Kolios · Damien Ernst
Information Design in Multi-Agent Reinforcement Learning
Yue Lin · Wenhao Li · Hongyuan Zha · Baoxiang Wang
DIFFER:Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning
Xunhan Hu · Jian Zhao · Wengang Zhou · Ruili Feng · Houqiang Li
Diverse Conventions for Human-AI Collaboration
Bidipta Sarkar · Andy Shih · Dorsa Sadigh
How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization
Hai Zhang · Hang Yu · Junqiao Zhao · Di Zhang · xiao zhang · Hongtu Zhou · Chang Huang · Chen Ye
Egocentric Planning for Scalable Embodied Task Achievement
Xiatoian Liu · Hector Palacios · Christian Muise
Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates
Sarath Sreedharan · Michael Katz
On the Planning Abilities of Large Language Models - A Critical Investigation
Karthik Valmeekam · Matthew Marquez · Sarath Sreedharan · Subbarao Kambhampati
Percentile Criterion Optimization in Offline Reinforcement Learning
Cyrus Cousins · Elita Lobo · Marek Petrik · Yair Zick
Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning
James Queeney · Mouhacine Benosman
Train Hard, Fight Easy: Robust Meta Reinforcement Learning
Ido Greenberg · Shie Mannor · Gal Chechik · Eli Meirom
A Path to Simpler Models Starts With Noise
Lesia Semenova · Harry Chen · Ronald Parr · Cynthia Rudin
State2Explanation: Concept-Based Explanations to Benefit Agent Learning and User Understanding
Devleena Das · Sonia Chernova · Been Kim
Disentangling Cognitive Diagnosis with Limited Exercise Labels
Xiangzhi Chen · Le Wu · Fei Liu · Lei Chen · Kun Zhang · Richang Hong · Meng Wang
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
Zhengxuan Wu · Atticus Geiger · Thomas Icard · Christopher Potts · Noah Goodman
Renku: a platform for sustainable data science
Rok Roškar · Chandrasekhar Ramakrishnan · Michele Volpi · Fernando Perez-Cruz · Lilian Gasser · Firat Ozdemir · Patrick Paitz · Mohammad Alisafaee · Philipp Fischer · Ralf Grubenmann · Eliza Harris · Tasko Olevski · Carl Remlinger · Luis Salamanca · Elisabet Capon Garcia · Lorenzo Cavazzi · Jakub Chrobasik · Darlin Cordoba Osnas · Alessandro Degano · Jimena Dupre · Wesley Johnson · Eike Kettner · Laura Kinkead · Sean Murphy · Flora Thiebaut · Olivier Verscheure
REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths
Xu Chen · Jingsen Zhang · Lei Wang · Quanyu Dai · Zhenhua Dong · Ruiming Tang · Rui Zhang · Li Chen · Xin Zhao · Ji-Rong Wen
OpenDataVal: a Unified Benchmark for Data Valuation
Kevin Jiang · Weixin Liang · James Zou · Yongchan Kwon
SmoothHess: ReLU Network Feature Interactions via Stein's Lemma
Max Torop · Aria Masoomi · Davin Hill · Kivanc Kose · Stratis Ioannidis · Jennifer Dy
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance
Jonathan Crabbé · Mihaela van der Schaar
Towards a fuller understanding of neurons with Clustered Compositional Explanations
Biagio La Rosa · Leilani Gilpin · Roberto Capobianco
GLIME: General, Stable and Local LIME Explanation
Zeren Tan · Yang Tian · Jian Li
StateMask: Explaining Deep Reinforcement Learning through State Mask
Zelei Cheng · Xian Wu · Jiahao Yu · Wenhai Sun · Wenbo Guo · Wenbo Guo · Xinyu Xing
Curve Your Enthusiasm: Concurvity Regularization in Differentiable Generalized Additive Models
Julien Siems · Konstantin Ditschuneit · Winfried Ripken · Alma Lindborg · Maximilian Schambach · Johannes Otterbach · Martin Genzel
Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models
Peter Hase · Mohit Bansal · Been Kim · Asma Ghandeharioun
SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis
Yuanshao Zhu · Yongchao Ye · Ying Wu · Xiangyu Zhao · James Yu
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
Junghyun Lee · Hanseul Cho · Se-Young Yun · Chulhee Yun
Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network
Hatef Otroshi Shahreza · Sébastien Marcel
Participatory Personalization in Classification
Hailey Joren · Chirag Nagpal · Katherine Heller · Berk Ustun
Stable Bias: Evaluating Societal Representations in Diffusion Models
Sasha Luccioni · Christopher Akiki · Margaret Mitchell · Yacine Jernite
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
Jacy Anthis · Victor Veitch
Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing
Ziyan Wang · Hao Wang
Gaussian Differential Privacy on Riemannian Manifolds
Yangdi Jiang · Xiaotian Chang · Yi Liu · Lei Ding · Linglong Kong · Bei Jiang
Better Private Linear Regression Through Better Private Feature Selection
Travis Dick · Jennifer Gillenwater · Matthew Joseph
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information
Kiwan Maeng · Chuan Guo · Sanjay Kariyappa · Sanjay Kariyappa · G. Edward Suh
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
Jimmy Di · Jack Douglas · Jayadev Acharya · Gautam Kamath · Ayush Sekhari
The Target-Charging Technique for Privacy Analysis across Interactive Computations
Edith Cohen · Xin Lyu
Differentially Private Image Classification by Learning Priors from Random Processes
Xinyu Tang · Ashwinee Panda · Vikash Sehwag · Prateek Mittal
Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning
Georgios Kaissis · Alexander Ziller · Stefan Kolek · Anneliese Riess · Daniel Rueckert
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations
Edward Raff · Amol Khanna · Fred Lu
Differentially Private Approximate Near Neighbor Counting in High Dimensions
Alexandr Andoni · Piotr Indyk · Sepideh Mahabadi · Shyam Narayanan
Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization
Adel Javanmard · Vahab Mirrokni
Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference
Ran Ran · Nuo Xu · Tao Liu · Wei Wang · Gang Quan · Wujie Wen
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference
Hongwu Peng · Ran Ran · Yukui Luo · Jiahui Zhao · Shaoyi Huang · Kiran Thorat · Tong Geng · Chenghong Wang · Xiaolin Xu · Wujie Wen · Caiwen Ding
On Differentially Private Sampling from Gaussian and Product Distributions
Badih Ghazi · Xiao Hu · Ravi Kumar · Pasin Manurangsi
Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images
Yuxin Wen · John Kirchenbauer · Jonas Geiping · Tom Goldstein
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
Boxin Wang · Weixin Chen · Hengzhi Pei · Chulin Xie · Mintong Kang · Chenhui Zhang · Chejian Xu · Zidi Xiong · Ritik Dutta · Rylan Schaeffer · Sang Truong · Simran Arora · Mantas Mazeika · Dan Hendrycks · Zinan Lin · Yu Cheng · Sanmi Koyejo · Dawn Song · Bo Li
TRIAGE: Characterizing and auditing training data for improved regression
Nabeel Seedat · Jonathan Crabbé · Zhaozhi Qian · Mihaela van der Schaar
ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP
Lu Yan · Zhuo Zhang · Guanhong Tao · Kaiyuan Zhang · Xuan Chen · Guangyu Shen · Xiangyu Zhang
RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning Attacks
Haonan Yan · Wenjing Zhang · Qian Chen · Xiaoguang Li · Wenhai Sun · HUI LI · Xiaodong Lin
ProPILE: Probing Privacy Leakage in Large Language Models
Siwon Kim · Sangdoo Yun · Hwaran Lee · Martin Gubri · Sungroh Yoon · Seong Joon Oh
Where Did I Come From? Origin Attribution of AI-Generated Images
Zhenting Wang · Chen Chen · Yi Zeng · Lingjuan Lyu · Shiqing Ma · Shiqing Ma
Stability Guarantees for Feature Attributions with Multiplicative Smoothing
Anton Xue · Rajeev Alur · Eric Wong
Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features
Mingli Zhu · Shaokui Wei · Hongyuan Zha · Baoyuan Wu
Black-box Backdoor Defense via Zero-shot Image Purification
Yucheng Shi · Mengnan Du · Xuansheng Wu · Zihan Guan · Jin Sun · Ninghao Liu
UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation
Muchao Ye · Ziyi Yin · Tianrong Zhang · Tianyu Du · Tianyu Du · Jinghui Chen · Ting Wang · Fenglong Ma
TempME: Towards the Explainability of Temporal Graph Neural Networks via Motif Discovery
Jialin Chen · Rex Ying
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?
Fnu Suya · Xiao Zhang · Yuan Tian · David Evans
Punctuation-level Attack: Single-shot and Single Punctuation Can Fool Text Models
wenqiang wang · Chongyang Du · Tao Wang · Kaihao Zhang · Wenhan Luo · Lin Ma · Wei Liu · Xiaochun Cao
Selective Sampling and Imitation Learning via Online Regression
Ayush Sekhari · Karthik Sridharan · Wen Sun · Runzhe Wu
Contextual Bandits and Imitation Learning with Preference-Based Active Queries
Ayush Sekhari · Karthik Sridharan · Wen Sun · Runzhe Wu
Learning Domain-Aware Detection Head with Prompt Tuning
Haochen Li · Rui Zhang · Hantao Yao · Xinkai Song · Yifan Hao · Yongwei Zhao · Ling Li · Yunji Chen
SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
Taesik Gong · Yewon Kim · Taeckyung Lee · Sorn Chottananurak · Sung-Ju Lee
Subspace Identification for Multi-Source Domain Adaptation
Zijian Li · Ruichu Cai · Guangyi Chen · Boyang Sun · Zhifeng Hao · Kun Zhang
A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging
Rui Wang · Yanyan Ouyang · Yu Panpan · Wangli Xu
Global Identifiability of $\ell_1$-based Dictionary Learning via Matrix Volume Optimization
Jingzhou Hu · Kejun Huang
Mode Connectivity in Auction Design
Christoph Hertrich · Yixin Tao · László A. Végh
Persuading Farsighted Receivers in MDPs: the Power of Honesty
Martino Bernasconi · Matteo Castiglioni · Alberto Marchesi · Mirco Mutti
Logarithmic-Regret Quantum Learning Algorithms for Zero-Sum Games
Minbo Gao · Zhengfeng Ji · Tongyang Li · Qisheng Wang
Is Learning in Games Good for the Learners?
William Brown · Jon Schneider · Kiran Vodrahalli
Fair Allocation of Indivisible Chores: Beyond Additive Costs
Bo Li · Fangxiao Wang · Yu Zhou
The Equivalence of Dynamic and Strategic Stability under Regularized Learning in Games
Victor Boone · Panayotis Mertikopoulos
Supply-Side Equilibria in Recommender Systems
Meena Jagadeesan · Nikhil Garg · Jacob Steinhardt
Efficient Subgame Refinement for Extensive-form Games
Zhenxing Ge · Zheng Xu · Tianyu Ding · Wenbin Li · Yang Gao
Data Market Design through Deep Learning
Sai Srivatsa Ravindranath · Yanchen Jiang · David Parkes
On the Interplay between Social Welfare and Tractability of Equilibria
Ioannis Anagnostides · Tuomas Sandholm
List and Certificate Complexities in Replicable Learning
Peter Dixon · A. Pavan · Jason Vander Woude · N. V. Vinodchandran
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
Ilias Diakonikolas · Jelena Diakonikolas · Daniel Kane · Puqian Wang · Nikos Zarifis
Learning Mixtures of Gaussians Using the DDPM Objective
Kulin Shah · Sitan Chen · Adam Klivans
Can semi-supervised learning use all the data effectively? A lower bound perspective
Alexandru Tifrea · Gizem Yüce · Amartya Sanyal · Fanny Yang
Recovering Unbalanced Communities in the Stochastic Block Model with Application to Clustering with a Faulty Oracle
Chandra Sekhar Mukherjee · Pan Peng · Jiapeng Zhang
Feature Adaptation for Sparse Linear Regression
Jonathan Kelner · Frederic Koehler · Raghu Meka · Dhruv Rohatgi
Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff
Arthur Jacot
Agnostically Learning Single-Index Models using Omnipredictors
Aravind Gollakota · Parikshit Gopalan · Adam Klivans · Konstantinos Stavropoulos
A unified framework for information-theoretic generalization bounds
Yifeng Chu · Maxim Raginsky
Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints
Jayadev Acharya · Clément L Canonne · Ziteng Sun · Himanshu Tyagi
Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
Saghar Adler · Vijay Subramanian
Regularization properties of adversarially-trained linear regression
Antonio Ribeiro · Dave Zachariah · Francis Bach · Thomas Schön
A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning
Nika Haghtalab · Michael Jordan · Eric Zhao
A Theory of Unsupervised Translation Motivated by Understanding Animal Communication
Shafi Goldwasser · David Gruber · Adam Tauman Kalai · Orr Paradise
Generalization in the Face of Adaptivity: A Bayesian Perspective
Moshe Shenfeld · Katrina Ligett
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning
Alicia Curth · Alan Jeffares · Mihaela van der Schaar
Smoothed Analysis of Sequential Probability Assignment
Alankrita Bhatt · Nika Haghtalab · Abhishek Shetty
A Batch-to-Online Transformation under Random-Order Model
Jing Dong · Yuichi Yoshida
Adversarial Attacks on Online Learning to Rank with Click Feedback
Jinhang Zuo · Zhiyao Zhang · Zhiyong Wang · Shuai Li · Mohammad Hajiesmaili · Adam Wierman
No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling
Eric Neyman · Tim Roughgarden
High-dimensional Contextual Bandit Problem without Sparsity
Junpei Komiyama · Masaaki Imaizumi
Online Convex Optimization with Unbounded Memory
Raunak Kumar · Sarah Dean · Robert Kleinberg
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits
Dorian Baudry · Fabien Pesquerel · Rémy Degenne · Odalric-Ambrym Maillard
Practical Contextual Bandits with Feedback Graphs
Mengxiao Zhang · Yuheng Zhang · Olga Vrousgou · Haipeng Luo · Paul Mineiro
On the Minimax Regret for Online Learning with Feedback Graphs
Khaled Eldowa · Emmanuel Esposito · Tom Cesari · Nicolò Cesa-Bianchi
Dynamic Pricing and Learning with Bayesian Persuasion
Shipra Agrawal · Yiding Feng · Wei Tang
Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
Subhojyoti Mukherjee · Qiaomin Xie · Josiah Hanna · Robert Nowak
Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk
David Simchi-Levi · Zeyu Zheng · Feng Zhu
Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima
Dongkuk Si · Chulhee Yun
Tight Risk Bounds for Gradient Descent on Separable Data
Matan Schliserman · Tomer Koren
The probability flow ODE is provably fast
Sitan Chen · Sinho Chewi · Holden Lee · Yuanzhi Li · Jianfeng Lu · Adil Salim
Matrix Compression via Randomized Low Rank and Low Precision Factorization
Rajarshi Saha · Varun Srivastava · Mert Pilanci
Optimistic Active Exploration of Dynamical Systems
Bhavya · Lenart Treven · Cansu Sancaktar · Sebastian Blaes · Stelian Coros · Andreas Krause
When is Agnostic Reinforcement Learning Statistically Tractable?
Zeyu Jia · Gene Li · Alexander Rakhlin · Ayush Sekhari · Nati Srebro
Online RL in Linearly $q^\pi$-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore
Gellert Weisz · András György · Csaba Szepesvari
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes
Emmeran Johnson · Ciara Pike-Burke · Patrick Rebeschini
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback
Han Shao · Lee Cohen · Avrim Blum · Yishay Mansour · Aadirupa Saha · Matthew Walter
Provably (More) Sample-Efficient Offline RL with Options
Xiaoyan Hu · Ho-fung Leung
Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
Shangtong Zhang · Remi Tachet des Combes · Romain Laroche
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
Laixi Shi · Gen Li · Yuting Wei · Yuxin Chen · Matthieu Geist · Yuejie Chi
Evaluating Self-Supervised Learning for Molecular Graph Embeddings
Hanchen Wang · Jean Kaddour · Shengchao Liu · Jian Tang · Joan Lasenby · Qi Liu
End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics
Alexander Shmakov · Kevin Greif · Michael Fenton · Aishik Ghosh · Pierre Baldi · Daniel Whiteson
Near Optimal Reconstruction of Spherical Harmonic Expansions
Amir Zandieh · Insu Han · Haim Avron
Distribution-Free Statistical Dispersion Control for Societal Applications
Zhun Deng · Thomas Zollo · Jake Snell · Toniann Pitassi · Richard Zemel
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs
Adam Cobb · Anirban Roy · Daniel Elenius · Frederick Heim · Brian Swenson · Sydney Whittington · James Walker · Theodore Bapty · Joseph Hite · Karthik Ramani · Christopher McComb · Susmit Jha
BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information
Mehran Kazemi · Quan Yuan · Deepti Bhatia · Najoung Kim · Xin Xu · Vaiva Imbrasaite · Deepak Ramachandran
Provably Efficient Algorithm for Nonstationary Low-Rank MDPs
Yuan Cheng · Jing Yang · Yingbin Liang
Locality-Aware Generalizable Implicit Neural Representation
Doyup Lee · Doyup Lee · Chiheon Kim · Minsu Cho · WOOK SHIN HAN
DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models
XiMing Xing · Chuang Wang · Chuang Wang · Haitao Zhou · Jing Zhang · Qian Yu · Dong Xu
Understanding and Mitigating Copying in Diffusion Models
Gowthami Somepalli · Vasu Singla · Micah Goldblum · Jonas Geiping · Tom Goldstein
On the Sublinear Regret of GP-UCB
Justin Whitehouse · Aaditya Ramdas · Steven Wu
Maximum State Entropy Exploration using Predecessor and Successor Representations
Arnav Kumar Jain · Lucas Lehnert · Irina Rish · Glen Berseth
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization
Kaiyue Wen · Zhiyuan Li · Tengyu Ma
Revisit Weakly-Supervised Audio-Visual Video Parsing from the Language Perspective
Yingying Fan · Yu Wu · Bo Du · Yutian Lin
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting
Zongsheng Yue · Jianyi Wang · Chen Change Loy
May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations
Rui Feng · Qi Zhu · Huan Tran · Binghong Chen · Aubrey Toland · Rampi Ramprasad · Chao Zhang
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning
Valeriia Cherepanova · Roman Levin · Gowthami Somepalli · Jonas Geiping · C. Bayan Bruss · Andrew Wilson · Tom Goldstein · Micah Goldblum
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model
Yizhe Zhang · Jiatao Gu · Zhuofeng Wu · Shuangfei Zhai · Joshua Susskind · Navdeep Jaitly
TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph
Xueyuan Lin · Haihong E · Chengjin Xu · Gengxian Zhou · Haoran Luo · Tianyi Hu · Fenglong Su · Ningyuan Li · Mingzhi Sun
The Best of Both Worlds in Network Population Games: Reaching Consensus and Convergence to Equilibrium
Shuyue Hu · Harold Soh · Georgios Piliouras
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks
Spencer Frei · Spencer Frei · Gal Vardi · Peter Bartlett · Nati Srebro
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics
Kamélia Daudel · Joe Benton · Yuyang Shi · Arnaud Doucet
Data-Informed Geometric Space Selection
Shuai Zhang · Wenqi Jiang
Degraded Polygons Raise Fundamental Questions of Neural Network Perception
Leonard Tang · Dan Ley
Language Model Alignment with Elastic Reset
Michael Noukhovitch · Samuel Lavoie · Florian Strub · Aaron Courville
DISCS: A Benchmark for Discrete Sampling
Katayoon Goshvadi · Haoran Sun · Xingchao Liu · Azade Nova · Ruqi Zhang · Will Grathwohl · Dale Schuurmans · Hanjun Dai
Should We Learn Most Likely Functions or Parameters?
Shikai Qiu · Tim G. J. Rudner · Sanyam Kapoor · Andrew Wilson
Certification of Distributional Individual Fairness
Matthew Wicker · Vihari Piratla · Adrian Weller
Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models
Siu Lun Chau · Krikamol Muandet · Dino Sejdinovic
Norm-based Generalization Bounds for Sparse Neural Networks
Tomer Galanti · Mengjia Xu · Liane Galanti · Tomaso Poggio
Exploring Why Object Recognition Performance Degrades Across Income Levels and Geographies with Factor Annotations
Laura Gustafson · Megan Richards · Melissa Hall · Caner Hazirbas · Diane Bouchacourt · Mark Ibrahim
Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
Yonghan Jung · Ivan Diaz · Jin Tian · Elias Bareinboim
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models
Deepak Narayanan · Keshav Santhanam · Peter Henderson · Peter Henderson · Rishi Bommasani · Tony Lee · Percy Liang
MCUFormer: Deploying Vision Tranformers on Microcontrollers with Limited Memory
Yinan Liang · Ziwei Wang · Xiuwei Xu · Yansong Tang · Jie Zhou · Jiwen Lu
Reproducibility Study of ”CartoonX: Cartoon Explanations of Image Classifiers”
Aditya Patra · Sina Taslimi · Luke Chin A Foeng · Pratik Kayal
Reproducibility study of 'Proto2Proto: Can you recognise the car, the way I do?'
Gerson de Kleuver · David Bikker · Wenhua Hu · Bram Veenman
Mitigating Source Bias for Fairer Weak Supervision
Changho Shin · Sonia Cromp · Dyah Adila · Frederic Sala
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
Cole Gulino · Justin Fu · Wenjie Luo · George Tucker · Eli Bronstein · Yiren Lu · Jean Harb · Xinlei Pan · Yan Wang · Xiangyu Chen · John Co-Reyes · Rishabh Agarwal · Rebecca Roelofs · Yao Lu · Nico Montali · Paul Mougin · Zoey Yang · Brandyn White · Aleksandra Faust · Rowan McAllister · Dragomir Anguelov · Benjamin Sapp
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy
Dongmin Park · Seola Choi · Doyoung Kim · Hwanjun Song · Jae-Gil Lee
[Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods
Domen Mohorčič · David Ocepek
Monte Carlo Tree Search with Boltzmann Exploration
Michael Painter · Mohamed Baioumy · Nick Hawes · Bruno Lacerda
[Re] VAE Approximation Error: ELBO and Exponential Families
Volodymyr Kyrylov · Navdeep Singh Bedi · Qianbo Zang
NeuroEvoBench: Benchmarking Evolutionary Optimizers for Deep Learning Applications
Robert Lange · Yujin Tang · Yingtao Tian
Holistic Evaluation of Text-to-Image Models
Tony Lee · Michihiro Yasunaga · Chenlin Meng · Yifan Mai · Joon Sung Park · Agrim Gupta · Yunzhi Zhang · Deepak Narayanan · Hannah Teufel · Marco Bellagente · Minguk Kang · Taesung Park · Jure Leskovec · Jun-Yan Zhu · Fei-Fei Li · Jiajun Wu · Stefano Ermon · Percy Liang
HT-Step: Aligning Instructional Articles with How-To Videos
Triantafyllos Afouras · Effrosyni Mavroudi · Tushar Nagarajan · Huiyu Wang · Lorenzo Torresani
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Invited Talk
2:15 PM - 3:05 PM

The world presents massive amounts of data for learning but the data relevant to any one thing or event is sparse. I will present evidence from the egocentric experiences of infants and young children in daily lives at home that demonstrate this sparsity, focusing on the case of early visual object recognition and object name learning. I will show how the statistics of infant self-generated experiences present solutions to the problem: learner control and optimization of the input, a developmentally constrained curriculum of spatial and temporal properties of the input, and the coherence statistics of individual episodes of experience. I will present evidence with respect to both low-level visual statistics and higher-level semantic categories. I conclude with a discussion of the alliance of the neural mechanisms that generate the statistics at any point in development and the neural mechanisms do the learning. I will the implications of the findings for artificial intelligence including studies using infant egocentric experiences as training data.

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Speaker Bio
Linda Smith
Linda B. Smith, Distinguished Professor at Indiana University Bloomington, is an internationally recognized leader in cognitive science and cognitive development. Taking a complex systems perspective, she seeks to understand the interdependencies among perceptual, motor and cognitive developments during the first three years of post-natal life. Using wearable sensors, including head-mounted cameras, she studies how the young learner’s own behavior creates the statistical structure of the learning environments with a current focus on developmentally changing visual statistics at the scale of everyday life and their role in motor, perceptual, and language development. The work has led to novel insights about the statistics of self-generated experiences and their role in rapid learning and innovative generalization from sparse and limited experience and challenges current massive-data approaches in AI. The work also motivates her current efforts on defining and promoting a precision (or individualized) developmental science, one that determines the multiple causes and interacting factors that create children’s individual developmental pathways. Smith received her PhD from the University of Pennsylvania in 1977 and immediately joined the faculty at Indiana University. Her work has been continuously funded by the National Science Foundation and/or the National Institutes of Health since 1978. She won the David E. Rumelhart Prize for Theoretical Contributions to Cognitive Science, the American Psychological Association Award for Distinguished Scientific Contributions, the William James Fellow Award from the American Psychological Society, the Norman Anderson Lifetime Achievement Award, and the Koffka Medal. She is an elected member of both the National Academy of Sciences and the American Academy of Arts and Science.
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Test Of Time

Test of Time Award Talk:Distributed Representations of Words and Phrases and their Compositionality

Tomas Mikolov · Ilya Sutskever · Kai Chen · Greg Corrado · Jeff Dean
3:05 PM - 3:25 PM

The recently introduced continuous Skip-gram model is an efficient method for learning high-quality distributed vector representations that capture a large number of precise syntactic and semantic word relationships. In this paper we present several improvements that make the Skip-gram model more expressive and enable it to learn higher quality vectors more rapidly. We show that by subsampling frequent words we obtain significant speedup, and also learn higher quality representations as measured by our tasks. We also introduce Negative Sampling, a simplified variant of Noise Contrastive Estimation (NCE) that learns more accurate vectors for frequent words compared to the hierarchical softmax. An inherent limitation of word representations is their indifference to word order and their inability to represent idiomatic phrases. For example, the meanings of Canada'' and "Air'' cannot be easily combined to obtain "Air Canada''. Motivated by this example, we present a simple and efficient method for finding phrases, and show that their vector representations can be accurately learned by the Skip-gram model.

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Creative AI Session 1

Jean Oh · Isabelle Guyon
3:05 PM - 3:40 PM
10 Events in this session
Kiss/Crash
Adam Cole
Blabrecs: An AI-Based Game of Nonsense Word Creation
Max Kreminski · Isaac Karth
Androgynous and Mixed Race Human Face
Eunsu Kang
Voice Scroll
David R Rokeby
The WHOOPS! Gallery: An Intersection of AI, Creativity, and the Unusual
Jack Hessel · · Yonatan Bitton · Nitzan Bitton Guetta · Yuval Elovici
Visions of Resilience: Augmented Diversity
Ninon Lizé Masclef
salad bowl
AI Applications to Illustrate Native American Arts: Birdsongs: Using Transfer Learning to Augment Image Generation Models
Kimberly Mann Bruch
Visualising AI
Emma Yousif · Ross West · Gaby Pearl
Creating playful comics together with AI
Yana Knight
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Oral
3:40 PM - 4:40 PM
4 Events in this session
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture
Dan Fu · Simran Arora · Jessica Grogan · Isys Johnson · Evan Sabri Eyuboglu · Armin Thomas · Benjamin Spector · Michael Poli · Atri Rudra · Christopher Ré
QLoRA: Efficient Finetuning of Quantized LLMs
Tim Dettmers · Artidoro Pagnoni · Ari Holtzman · Luke Zettlemoyer
Scaling Data-Constrained Language Models
Niklas Muennighoff · Alexander Rush · Boaz Barak · Teven Le Scao · Nouamane Tazi · Aleksandra Piktus · Sampo Pyysalo · Thomas Wolf · Colin Raffel
Bridging Discrete and Backpropagation: Straight-Through and Beyond
Liyuan Liu · Chengyu Dong · Xiaodong Liu · Bin Yu · Jianfeng Gao
Go to Event Page
Oral
3:40 PM - 4:40 PM
4 Events in this session
Nearly Tight Bounds For Differentially Private Multiway Cut
Mina Dalirrooyfard · Slobodan Mitrovic · Yuriy Nevmyvaka
Privacy Auditing with One (1) Training Run
Thomas Steinke · Milad Nasr · Matthew Jagielski
Private Everlasting Prediction
Moni Naor · Kobbi Nissim · Uri Stemmer · Chao Yan
User-Level Differential Privacy With Few Examples Per User
Badih Ghazi · Pritish Kamath · Ravi Kumar · Pasin Manurangsi · Raghu Meka · Chiyuan Zhang
Go to Event Page
Oral
3:40 PM - 4:40 PM
4 Events in this session
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Simon Buchholz · Goutham Rajendran · Elan Rosenfeld · Bryon Aragam · Bernhard Schölkopf · Pradeep Ravikumar
A Measure-Theoretic Axiomatisation of Causality
Junhyung Park · Simon Buchholz · Bernhard Schölkopf · Krikamol Muandet
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects
Ahmed Alaa · Zaid Ahmad · Mark van der Laan
Causal normalizing flows: from theory to practice
Adrián Javaloy · Pablo Sanchez-Martin · Isabel Valera
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Oral
3:40 PM - 4:40 PM
4 Events in this session
Rotating Features for Object Discovery
Sindy Löwe · Phillip Lippe · Francesco Locatello · Max Welling
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment
Royi Rassin · Eran Hirsch · Daniel Glickman · Shauli Ravfogel · Yoav Goldberg · Gal Chechik
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
Sébastien Lachapelle · Divyat Mahajan · Ioannis Mitliagkas · Simon Lacoste-Julien
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
Tianqin Li · Ziqi Wen · Yangfan Li · Tai Sing Lee
Go to Event Page
Poster
5:15 PM - 7:15 PM
588 Events in this session
A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability
Zijie Geng · Xijun Li · Jie Wang · Xiao Li · Yongdong Zhang · Feng Wu
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation
Wengong Jin · Siranush Sarkizova · Xun Chen · Nir HaCohen · Caroline Uhler
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning
Mohammadamin Tavakoli · Pierre Baldi · Ann Marie Carlton · Yin Ting Chiu · Alexander Shmakov · David Van Vranken
Accelerating Molecular Graph Neural Networks via Knowledge Distillation
Filip Ekström Kelvinius · Dimitar Georgiev · Artur Toshev · Johannes Gasteiger
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials
Guillem Simeon · Gianni De Fabritiis
LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion
Jiaqi Guan · Xingang Peng · PeiQi Jiang · Yunan Luo · Jian Peng · Jianzhu Ma
GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising
Hyeonsu Kim · Jeheon Woo · SEONGHWAN KIM · Seokhyun Moon · Jun Hyeong Kim · Woo Youn Kim
Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics
Mathias Schreiner · Ole Winther · Simon Olsson
De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
Xiuyuan Hu · Guoqing Liu · Yang Zhao · Hao Zhang
Semantic segmentation of sparse irregular point clouds for leaf/wood discrimination
Yuchen BAI · Jean-Baptiste Durand · Grégoire Vincent · Florence Forbes
Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models
Zhong Yi Wan · Ricardo Baptista · Anudhyan Boral · Yi-Fan Chen · John Anderson · Fei Sha · Leonardo Zepeda-Núñez
StreamNet: Memory-Efficient Streaming Tiny Deep Learning Inference on the Microcontroller
Hong-Sheng Zheng · Yu-Yuan Liu · Chen-Fong Hsu · Tsung Tai Yeh
Adaptive Contextual Perception: How To Generalize To New Backgrounds and Ambiguous Objects
Zhuofan Ying · Peter Hase · Mohit Bansal
3D-Aware Visual Question Answering about Parts, Poses and Occlusions
Xingrui Wang · Wufei Ma · Zhuowan Li · Adam Kortylewski · Alan Yuille
Mip-Grid: Anti-aliased Grid Representations for Neural Radiance Fields
Seungtae Nam · Daniel Rho · Jong Hwan Ko · Eunbyung Park
MG-ViT: A Multi-Granularity Method for Compact and Efficient Vision Transformers
Yu Zhang · Yepeng Liu · Duoqian Miao · Qi Zhang · Yiwei Shi · Liang Hu
CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography
Jiwen Yu · Xuanyu Zhang · Youmin Xu · Jian Zhang
Lookup Table meets Local Laplacian Filter: Pyramid Reconstruction Network for Tone Mapping
Feng Zhang · Ming Tian · Zhiqiang Li · Bin Xu · Qingbo Lu · Changxin Gao · Nong Sang
SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs
Lijun Yu · Yong Cheng · Zhiruo Wang · Vivek Kumar · Wolfgang Macherey · Yanping Huang · David Ross · Irfan Essa · Yonatan Bisk · Ming-Hsuan Yang · Kevin Murphy · Alexander Hauptmann · Lu Jiang · Lu Jiang
PAPR: Proximity Attention Point Rendering
Yanshu Zhang · Shichong Peng · Alireza Moazeni · Ke Li
Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera
Lujie Xia · Ziluo Ding · Rui Zhao · Jiyuan Zhang · Lei Ma · Zhaofei Yu · Tiejun Huang · Ruiqin Xiong
Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects
Tianhang Cheng · Wei-Chiu Ma · Kaiyu Guan · Antonio Torralba · Shenlong Wang
Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP
Qihang Yu · Ju He · Xueqing Deng · Xiaohui Shen · Liang-Chieh Chen
Label-efficient Segmentation via Affinity Propagation
Wentong Li · Yuqian Yuan · Song Wang · Wenyu Liu · Dongqi Tang · Jian liu · Jianke Zhu · Lei Zhang
DAC-DETR: Divide the Attention Layers and Conquer
Zhengdong Hu · Yifan Sun · Jingdong Wang · Yi Yang
Mitigating the Effect of Incidental Correlations on Part-based Learning
Gaurav Bhatt · Deepayan Das · Leonid Sigal · Vineeth N Balasubramanian
Generative Category-level Object Pose Estimation via Diffusion Models
Jiyao Zhang · Mingdong Wu · Hao Dong
Tuning Multi-mode Token-level Prompt Alignment across Modalities
Dongsheng Wang · Miaoge Li · Xinyang Liu · MingSheng Xu · Bo Chen · Hanwang Zhang
Discovering Intrinsic Spatial-Temporal Logic Rules to Explain Human Actions
Chengzhi Cao · Chao Yang · Ruimao Zhang · Shuang Li
M$^{2}$SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors
Jonggyu Jang · Sangwoo Oh · Youjin Kim · Dongmin Seo · Youngchol Choi · Hyun Jong Yang
CamoPatch: An Evolutionary Strategy for Generating Camoflauged Adversarial Patches
Phoenix Williams · Ke Li
Decorate3D: Text-Driven High-Quality Texture Generation for Mesh Decoration in the Wild
Yanhui Guo · Xinxin Zuo · Peng Dai · Juwei Lu · Xiaolin Wu · Li cheng · Youliang Yan · Songcen Xu · Xiaofei Wu
DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field
Chenyangguang Zhang · Yan Di · Ruida Zhang · Guangyao Zhai · Fabian Manhardt · Federico Tombari · Xiangyang Ji
Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization
Jameel Abdul Samadh · Mohammad Hanan Gani · Noor Hussein · Muhammad Uzair Khattak · Muhammad Muzammal Naseer · Fahad Shahbaz Khan · Salman Khan
Compressed Video Prompt Tuning
Bing Li · Jiaxin Chen · Xiuguo Bao · Di Huang
ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction
Yixun Liang · Hao He · Yingcong Chen
Saving 100x Storage: Prototype Replay for Reconstructing Training Sample Distribution in Class-Incremental Semantic Segmentation
Jinpeng Chen · Runmin Cong · Yuxuan LUO · Horace Ip · Sam Kwong
Masked Image Residual Learning for Scaling Deeper Vision Transformers
Guoxi Huang · Hongtao Fu · Adrian G. Bors
LuminAIRe: Illumination-Aware Conditional Image Repainting for Lighting-Realistic Generation
Jiajun Tang · Haofeng Zhong · Shuchen Weng · Boxin Shi
Segment Anything in 3D with NeRFs
Jiazhong Cen · Zanwei Zhou · Jiemin Fang · chen yang · Wei Shen · Lingxi Xie · Dongsheng Jiang · XIAOPENG ZHANG · Qi Tian
Real-World Image Super-Resolution as Multi-Task Learning
Wenlong Zhang · Xiaohui Li · Guangyuan SHI · Xiangyu Chen · Yu Qiao · Xiaoyun Zhang · Xiao-Ming Wu · Chao Dong
VPGTrans: Transfer Visual Prompt Generator across LLMs
Ao Zhang · Hao Fei · Yuan Yao · Wei Ji · Li Li · Zhiyuan Liu · Tat-Seng Chua
What Do Deep Saliency Models Learn about Visual Attention?
Shi Chen · Ming Jiang · Qi Zhao
Mask Propagation for Efficient Video Semantic Segmentation
Yuetian Weng · Mingfei Han · Haoyu He · Mingjie Li · Lina Yao · Xiaojun Chang · Bohan Zhuang
Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark
Zhengfei Kuang · Yunzhi Zhang · Hong-Xing Yu · Samir Agarwala · Elliott / Shangzhe Wu · Jiajun Wu
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph Diffusion
Guangyao Zhai · Evin Pınar Örnek · Shun-Cheng Wu · Yan Di · Federico Tombari · Nassir Navab · Benjamin Busam
Towards Label-free Scene Understanding by Vision Foundation Models
Runnan Chen · Youquan Liu · Lingdong Kong · Nenglun Chen · Xinge ZHU · Yuexin Ma · Tongliang Liu · Wenping Wang
Real3D-AD: A Dataset of Point Cloud Anomaly Detection
Jiaqi Liu · Guoyang Xie · Ruitao Chen · Xinpeng Li · Jinbao Wang · Yong Liu · Chengjie Wang · Feng Zheng
Tame a Wild Camera: In-the-Wild Monocular Camera Calibration
Shengjie Zhu · Abhinav Kumar · Masa Hu · Xiaoming Liu
MixFormerV2: Efficient Fully Transformer Tracking
Yutao Cui · Tianhui Song · Gangshan Wu · Limin Wang
TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation
Rongkun Zheng · Lu Qi · Xi Chen · Yi Wang · Kun Wang · Yu Qiao · Hengshuang Zhao
Learning Neural Implicit through Volume Rendering with Attentive Depth Fusion Priors
Pengchong Hu · Zhizhong Han
Towards A Richer 2D Understanding of Hands at Scale
Tianyi Cheng · Dandan Shan · Ayda Hassen · Richard Higgins · David Fouhey
HotBEV: Hardware-oriented Transformer-based Multi-View 3D Detector for BEV Perception
Peiyan Dong · Zhenglun Kong · Xin Meng · Pinrui Yu · Yifan Gong · Geng Yuan · Hao Tang · Yanzhi Wang
QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution
Haotong Qin · Yulun Zhang · Yifu Ding · Yifan liu · Xianglong Liu · Martin Danelljan · Fisher Yu
ViSt3D: Video Stylization with 3D CNN
Ayush Pande · Gaurav Sharma
IDEA: An Invariant Perspective for Efficient Domain Adaptive Image Retrieval
Haixin Wang · Hao Wu · Jinan Sun · Shikun Zhang · Chong Chen · Xian-Sheng Hua · Xiao Luo
Uni3DETR: Unified 3D Detection Transformer
Zhenyu Wang · Ya-Li Li · Xi Chen · Hengshuang Zhao · Shengjin Wang
Training on Foveated Images Improves Robustness to Adversarial Attacks
Muhammad Shah · Aqsa Kashaf · Bhiksha Raj
Volume Feature Rendering for Fast Neural Radiance Field Reconstruction
Kang Han · Wei Xiang · Lu Yu
Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation
Jia-Xing Zhong · Ta-Ying Cheng · Yuhang He · Kai Lu · Kaichen Zhou · Andrew Markham · Niki Trigoni
From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
Peter Shaw · Mandar Joshi · James Cohan · Jonathan Berant · Panupong Pasupat · Hexiang Hu · Urvashi Khandelwal · Kenton Lee · Kristina N Toutanova
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning
kangyang Luo · Shuai Wang · Yexuan Fu · Xiang Li · Yunshi Lan · Ming Gao
SALSA VERDE: a machine learning attack on LWE with sparse small secrets
Cathy Li · Emily Wenger · Zeyuan Allen-Zhu · Francois Charton · Kristin E. Lauter
GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies
Takahiro Mimori · Michiaki Hamada
ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers
Pascal Notin · Ruben Weitzman · Debora Marks · Yarin Gal
PoET: A generative model of protein families as sequences-of-sequences
Timothy Truong Jr · Tristan Bepler
Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions
Ruofan Wu · Jiawei Qiao · Mingzhe Wu · Wen Yu · Ming Zheng · Tengfei LIU · Tianyi Zhang · Weiqiang Wang
Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias
Zhongwei Wan · Che Liu · Mi Zhang · Jie Fu · Benyou Wang · Sibo Cheng · Lei Ma · César Quilodrán-Casas · Rossella Arcucci
AVIS: Autonomous Visual Information Seeking with Large Language Model Agent
Ziniu Hu · Ahmet Iscen · Chen Sun · Kai-Wei Chang · Yizhou Sun · David Ross · Cordelia Schmid · Alireza Fathi
The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs
Laura Ruis · Akbir Khan · Stella Biderman · Sara Hooker · Tim Rocktäschel · Edward Grefenstette
Composing Parameter-Efficient Modules with Arithmetic Operation
Jinghan Zhang · shiqi chen · Junteng Liu · Junxian He
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning
Pei Chen · Soumajyoti Sarkar · Leonard Lausen · Balasubramaniam Srinivasan · Sheng Zha · Ruihong Huang · George Karypis
Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing
Yongrui Chen · Shenyu Zhang · Guilin Qi · Xinnan Guo
Augmenting Language Models with Long-Term Memory
Weizhi Wang · Li Dong · Hao Cheng · Xiaodong Liu · Xifeng Yan · Jianfeng Gao · Furu Wei
CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society
Guohao Li · Hasan Hammoud · Hani Itani · Dmitrii Khizbullin · Bernard Ghanem
Large language models transition from integrating across position-yoked, exponential windows to structure-yoked, power-law windows
David Skrill · Samuel Norman-Haignere
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
Noah Hollmann · Samuel Müller · Frank Hutter
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
Jiawei Liu · Chunqiu Steven Xia · Yuyao Wang · LINGMING ZHANG
Birth of a Transformer: A Memory Viewpoint
Alberto Bietti · Vivien Cabannes · Diane Bouchacourt · Herve Jegou · Leon Bottou
Fine-Grained Human Feedback Gives Better Rewards for Language Model Training
Zeqiu Wu · Yushi Hu · Weijia Shi · Nouha Dziri · Alane Suhr · Prithviraj Ammanabrolu · Noah Smith · Mari Ostendorf · Hannaneh Hajishirzi
AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
Tong Wu · Zhihao Fan · Xiao Liu · Hai-Tao Zheng · Yeyun Gong · yelong shen · Jian Jiao · Juntao Li · zhongyu wei · Jian Guo · Nan Duan · Weizhu Chen
Preference-grounded Token-level Guidance for Language Model Fine-tuning
Shentao Yang · Shujian Zhang · Congying Xia · Yihao Feng · Caiming Xiong · Mingyuan Zhou
From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Models to Pre-trained Machine Reader
Weiwen Xu · Xin Li · Wenxuan Zhang · Meng Zhou · Wai Lam · Luo Si · Lidong Bing
Grammar Prompting for Domain-Specific Language Generation with Large Language Models
Bailin Wang · Zi Wang · Xuezhi Wang · Yuan Cao · Rif A. Saurous · Yoon Kim
Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts
Eduard Tulchinskii · Kristian Kuznetsov · Laida Kushnareva · Daniil Cherniavskii · Sergey Nikolenko · Evgeny Burnaev · Serguei Barannikov · Irina Piontkovskaya
ComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text Translation
Chenyang Le · Yao Qian · Long Zhou · Shujie LIU · Yanmin Qian · Michael Zeng · Xuedong Huang
Incomplete Multimodality-Diffused Emotion Recognition
Yuanzhi Wang · Yong Li · Zhen Cui
Self-Evaluation Guided Beam Search for Reasoning
Yuxi Xie · Kenji Kawaguchi · Yiran Zhao · James Xu Zhao · Min-Yen Kan · Junxian He · Michael Xie
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition
Aashaka Desai · Lauren Berger · Fyodor Minakov · Nessa Milano · Chinmay Singh · Kriston Pumphrey · Richard Ladner · Hal Daumé III · Alex X Lu · Naomi Caselli · Danielle Bragg
DOSE: Diffusion Dropout with Adaptive Prior for Speech Enhancement
Wenxin Tai · Yue Lei · Fan Zhou · Goce Trajcevski · Ting Zhong
Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data
Praveen Venkatesh · Corbett Bennett · Sam Gale · Tamina Ramirez · Greggory Heller · Severine Durand · Shawn Olsen · Stefan Mihalas
Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks
Yaoyu Zhu · Wei Fang · Xiaodong Xie · Tiejun Huang · Zhaofei Yu
Scaling laws for language encoding models in fMRI
Richard Antonello · Aditya Vaidya · Alexander Huth
Computing a human-like reaction time metric from stable recurrent vision models
Lore Goetschalckx · Lakshmi Narasimhan Govindarajan · Alekh Karkada Ashok · Aarit Ahuja · David Sheinberg · Thomas Serre
Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture
Galen Pogoncheff · Jacob Granley · Michael Beyeler
Energy Guided Diffusion for Generating Neurally Exciting Images
Pawel Pierzchlewicz · Konstantin Willeke · Arne Nix · Pavithra Elumalai · Kelli Restivo · Tori Shinn · Cate Nealley · Gabrielle Rodriguez · Saumil Patel · Katrin Franke · Andreas Tolias · Fabian Sinz
AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity
Jingyuan Li · Leo Scholl · Trung Le · Pavithra Rajeswaran · Amy Orsborn · Eli Shlizerman
Strong and Precise Modulation of Human Percepts via Robustified ANNs
Guy Gaziv · Michael Lee · James J DiCarlo
Convolution Monge Mapping Normalization for learning on sleep data
Théo Gnassounou · Rémi Flamary · Alexandre Gramfort
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity
Tianqin Li · Ziqi Wen · Yangfan Li · Tai Sing Lee
A normative theory of social conflict
Sergey Shuvaev · Evgeny Amelchenko · Dmitry Smagin · Natalia Kudryavtseva · Grigori Enikolopov · Alex Koulakov
Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity
Joel Ye · Jennifer Collinger · Leila Wehbe · Robert Gaunt
Large Language Models are Visual Reasoning Coordinators
Liangyu Chen · Bo Li · Sheng Shen · Jingkang Yang · Chunyuan Li · Kurt Keutzer · Trevor Darrell · Ziwei Liu
Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb
Jacob Zavatone-Veth · Paul Masset · William Tong · Joseph D. Zak · Venkatesh Murthy · Cengiz Pehlevan
Hierarchical VAEs provide a normative account of motion processing in the primate brain
Hadi Vafaii · Jacob Yates · Daniel Butts
Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis
Mitchell Ostrow · Adam Eisen · Leo Kozachkov · Ila Fiete
Joint processing of linguistic properties in brains and language models
SUBBAREDDY OOTA · Manish Gupta · Mariya Toneva
Spike-driven Transformer
Man Yao · Man Yao · JiaKui Hu · Zhaokun Zhou · Li Yuan · Yonghong Tian · Bo Xu · Guoqi Li
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
Rylan Schaeffer · Mikail Khona · Tzuhsuan Ma · Cristobal Eyzaguirre · Sanmi Koyejo · Ila Fiete
DeWave: Discrete Encoding of EEG Waves for EEG to Text Translation
Yiqun Duan · Charles Chau · Zhen Wang · Yu-Kai Wang · Chin-teng Lin
Training neural operators to preserve invariant measures of chaotic attractors
Ruoxi Jiang · Peter Y. Lu · Elena Orlova · Rebecca Willett
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability
Fabien Casenave · Brian Staber · Xavier Roynard
Solving Inverse Physics Problems with Score Matching
Benjamin Holzschuh · Simona Vegetti · Nils Thuerey
PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
Jihui Jin · Etienne Ollivier · Richard Touret · Matthew McKinley · Karim Sabra · Justin Romberg
Transformer-based Planning for Symbolic Regression
Parshin Shojaee · Kazem Meidani · Amir Barati Farimani · Chandan Reddy
Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model
Luning Sun · Xu Han · Han Gao · Jian-Xun Wang · Liping Liu
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning
Francesca Bartolucci · Emmanuel de Bézenac · Bogdan Raonic · Roberto Molinaro · Siddhartha Mishra · Rima Alaifari
Find What You Want: Learning Demand-conditioned Object Attribute Space for Demand-driven Navigation
Hongcheng Wang · Andy Guan Hong Chen · Xiaoqi Li · Mingdong Wu · Hao Dong
Online POMDP Planning with Anytime Deterministic Guarantees
Moran Barenboim · Vadim Indelman
Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills
Denis Blessing · Onur Celik · Xiaogang Jia · Xiaogang Jia · Moritz Reuss · Maximilian Li · Rudolf Lioutikov · Gerhard Neumann
Accelerating Motion Planning via Optimal Transport
An T. Le · Georgia Chalvatzaki · Armin Biess · Jan Peters
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
Arjun Majumdar · Karmesh Yadav · Sergio Arnaud · Jason Ma · Claire Chen · Sneha Silwal · Aryan Jain · Vincent-Pierre Berges · Tingfan Wu · Jay Vakil · Pieter Abbeel · Jitendra Malik · Dhruv Batra · Yixin Lin · Oleksandr Maksymets · Aravind Rajeswaran · Franziska Meier
POMDP Planning for Object Search in Partially Unknown Environment
Yongbo Chen · Hanna Kurniawati
FGPrompt: Fine-grained Goal Prompting for Image-goal Navigation
Xinyu Sun · Peihao Chen · Jugang Fan · Jian Chen · Thomas Li · Mingkui Tan
Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective
Zhiding Liu · Mingyue Cheng · Zhi Li · Zhi Li · Zhenya Huang · Qi Liu · Yanhu Xie · Enhong Chen
Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment
Yutong Xia · Yuxuan Liang · Haomin Wen · Xu Liu · Kun Wang · Zhengyang Zhou · Roger Zimmermann
Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
Yong Liu · Chenyu Li · Jianmin Wang · Mingsheng Long
Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation
Lisa Dunlap · Alyssa Umino · Han Zhang · Jiezhi Yang · Joseph Gonzalez · Trevor Darrell
HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
Bipasha Sen · Gaurav Singh · Aditya Agarwal · Rohith Agaram · Madhava Krishna · Srinath Sridhar
Meet in the Middle: A New Pre-training Paradigm
Anh Nguyen · Nikos Karampatziakis · Weizhu Chen
Lightweight Vision Transformer with Bidirectional Interaction
Qihang Fan · Huaibo Huang · Xiaoqiang Zhou · Ran He
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
Jeonghoon Kim · Jung Hyun Lee · Sungdong Kim · Joonsuk Park · Kang Min Yoo · Se Jung Kwon · Dongsoo Lee
Tanh Works Better with Asymmetry
Dongjin Kim · Woojeong Kim · Suhyun Kim
A General Framework for Equivariant Neural Networks on Reductive Lie Groups
Ilyes Batatia · Mario Geiger · Jose Munoz · Tess Smidt · Lior Silberman · Christoph Ortner
Clustering the Sketch: Dynamic Compression for Embedding Tables
Henry Tsang · Thomas Ahle
Systematic Visual Reasoning through Object-Centric Relational Abstraction
Taylor Webb · Shanka Subhra Mondal · Jonathan D Cohen
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
Peng Cui · Dan Zhang · Zhijie Deng · Yinpeng Dong · Jun Zhu
Bridging Discrete and Backpropagation: Straight-Through and Beyond
Liyuan Liu · Chengyu Dong · Xiaodong Liu · Bin Yu · Jianfeng Gao
Module-wise Training of Neural Networks via the Minimizing Movement Scheme
Skander Karkar · Ibrahim Ayed · Emmanuel de Bézenac · Patrick Gallinari
You Only Condense Once: Two Rules for Pruning Condensed Datasets
Yang He · Lingao Xiao · Joey Tianyi Zhou
Sharpness-Aware Minimization Leads to Low-Rank Features
Maksym Andriushchenko · Dara Bahri · Hossein Mobahi · Nicolas Flammarion
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
Yann Dubois · Chen Xuechen Li · Rohan Taori · Tianyi Zhang · Ishaan Gulrajani · Jimmy Ba · Carlos Guestrin · Percy Liang · Tatsunori Hashimoto
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture
Dan Fu · Simran Arora · Jessica Grogan · Isys Johnson · Evan Sabri Eyuboglu · Armin Thomas · Benjamin Spector · Michael Poli · Atri Rudra · Christopher Ré
Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantisation.
Chris Subia-Waud · Srinandan Dasmahapatra
ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection
Zhongzhan Huang · Pan Zhou · Pan Zhou · Shuicheng Yan · Liang Lin
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks
Sara Babakniya · Zalan Fabian · Chaoyang He · Mahdi Soltanolkotabi · Salman Avestimehr
Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training
Rie Johnson · Tong Zhang
Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity
Metod Jazbec · James Allingham · Dan Zhang · Eric Nalisnick
Accurate Interpolation for Scattered Data through Hierarchical Residual Refinement
Shizhe Ding · Boyang Xia · Dongbo Bu
Geometric Transformer with Interatomic Positional Encoding
Yusong Wang · Shaoning Li · Tong Wang · Bin Shao · Nanning Zheng · Tie-Yan Liu
Random-Access Infinite Context Length for Transformers
Amirkeivan Mohtashami · Martin Jaggi
Designing Robust Transformers using Robust Kernel Density Estimation
Xing Han · Tongzheng Ren · Tan Nguyen · Khai Nguyen · Joydeep Ghosh · Nhat Ho
Schema-learning and rebinding as mechanisms of in-context learning and emergence
Sivaramakrishnan Swaminathan · Antoine Dedieu · Rajkumar Vasudeva Raju · Murray Shanahan · Miguel Lazaro-Gredilla · Dileep George
Polyhedron Attention Module: Learning Adaptive-order Interactions
Tan Zhu · Fei Dou · Xinyu Wang · Jin Lu · Jinbo Bi
Coneheads: Hierarchy Aware Attention
Albert Tseng · Tao Yu · Toni Liu · Christopher De Sa
The Quantization Model of Neural Scaling
Eric Michaud · Ziming Liu · Uzay Girit · Max Tegmark
Pruning vs Quantization: Which is Better?
Andrey Kuzmin · Markus Nagel · Mart van Baalen · Arash Behboodi · Tijmen Blankevoort
QLoRA: Efficient Finetuning of Quantized LLMs
Tim Dettmers · Artidoro Pagnoni · Ari Holtzman · Luke Zettlemoyer
How a Student becomes a Teacher: learning and forgetting through Spectral methods
Lorenzo Giambagli · Lorenzo Buffoni · Lorenzo Chicchi · Duccio Fanelli
DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models
Weijia Wu · Yuzhong Zhao · Hao Chen · Yuchao Gu · Rui Zhao · Yefei He · Hong Zhou · Mike Zheng Shou · Chunhua Shen
TextDiffuser: Diffusion Models as Text Painters
Jingye Chen · Yupan Huang · Yupan Huang · Tengchao Lv · Lei Cui · Qifeng Chen · Furu Wei
A Unified Framework for U-Net Design and Analysis
Christopher Williams · Fabian Falck · George Deligiannidis · Chris C Holmes · Arnaud Doucet · Saifuddin Syed
Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
Tobias Schröder · Zijing Ou · Jen Lim · Yingzhen Li · Sebastian Vollmer · Andrew Duncan
Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States
Valerii Iakovlev · Markus Heinonen · Harri Lähdesmäki
Addressing Negative Transfer in Diffusion Models
Hyojun Go · Kim · Yunsung Lee · Seunghyun Lee · Shinhyeok Oh · Hyeongdon Moon · Seungtaek Choi
Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
Ethan Pronovost · Meghana Reddy Ganesina · Noureldin Hendy · Zeyu Wang · Andres Morales · Kai Wang · Nick Roy
PTQD: Accurate Post-Training Quantization for Diffusion Models
Yefei He · Luping Liu · Jing Liu · Weijia Wu · Hong Zhou · Bohan Zhuang
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport
Jaemoo Choi · Jaewoong Choi · Myungjoo Kang
Learning Energy-based Model via Dual-MCMC Teaching
Jiali Cui · Tian Han
In-Context Learning Unlocked for Diffusion Models
Zhendong Wang · Yifan Jiang · Yadong Lu · yelong shen · Pengcheng He · Weizhu Chen · Zhangyang "Atlas" Wang · Mingyuan Zhou
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach
Sangwoong Yoon · Young-Uk Jin · Yung-Kyun Noh · Frank Park
Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
kai wang · Fei Yang · Shiqi Yang · Shiqi Yang · Muhammad Atif Butt · Joost van de Weijer
Diffusion Model for Graph Inverse Problems: Towards Effective Source Localization on Complex Networks
Xin Yan · Hui Fang · Qiang He
DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics
Kaiwen Zheng · Cheng Lu · Jianfei Chen · Jun Zhu
AmadeusGPT: a natural language interface for interactive animal behavioral analysis
Shaokai Ye · Jessy Lauer · Mu Zhou · Alexander Mathis · Mackenzie Mathis
Optimal Transport-Guided Conditional Score-Based Diffusion Model
Xiang Gu · Liwei Yang · Jian Sun · Zongben Xu
Direct Diffusion Bridge using Data Consistency for Inverse Problems
Hyungjin Chung · Jeongsol Kim · Jong Chul Ye
DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models
Ying Fan · Olivia Watkins · Yuqing Du · Yuqing Du · Hao Liu · Moonkyung Ryu · Craig Boutilier · Pieter Abbeel · Mohammad Ghavamzadeh · Kangwook Lee · Kimin Lee
Complexity Matters: Rethinking the Latent Space for Generative Modeling
Tianyang Hu · Fei Chen · Haonan Wang · Jiawei Li · Wenjia Wang · Jiacheng Sun · Zhenguo Li
Im-Promptu: In-Context Composition from Image Prompts
Bhishma Dedhia · Michael Chang · Jake Snell · Tom Griffiths · Niraj Jha
Gaussian Mixture Solvers for Diffusion Models
Hanzhong Guo · Cheng Lu · Fan Bao · Tianyu Pang · Shuicheng Yan · Chao Du · Chongxuan LI
Score-based Generative Modeling through Stochastic Evolution Equations in Hilbert Spaces
Sungbin Lim · EUN BI YOON · Taehyun Byun · Taewon Kang · Seungwoo Kim · Kyungjae Lee · Sungjoon Choi
Projection Regret: Reducing Background Bias for Novelty Detection via Diffusion Models
Sungik Choi · Hankook Lee · Honglak Lee · Moontae Lee
Score-based Source Separation with Applications to Digital Communication Signals
Tejas Jayashankar · Gary C.F. Lee · Alejandro Lancho · Amir Weiss · Yury Polyanskiy · Gregory Wornell
Recommender Systems with Generative Retrieval
Shashank Rajput · Nikhil Mehta · Anima Singh · Raghunandan Hulikal Keshavan · Trung Vu · Lukasz Heldt · Lichan Hong · Yi Tay · Vinh Tran · Jonah Samost · Maciej Kula · Ed Chi · Maheswaran Sathiamoorthy
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
George Stein · Jesse Cresswell · Rasa Hosseinzadeh · Yi Sui · Brendan Ross · Valentin Villecroze · Zhaoyan Liu · Anthony Caterini · Eric Taylor · Gabriel Loaiza-Ganem
Divide, Evaluate, and Refine: Evaluating and Improving Text-to-Image Alignment with Iterative VQA Feedback
Jaskirat Singh · Liang Zheng
Towards Efficient Image Compression Without Autoregressive Models
Muhammad Salman Ali · Yeongwoong Kim · Maryam Qamar · Sung-Chang Lim · Donghyun Kim · Chaoning Zhang · Sung-Ho Bae · Hui Yong Kim
Idempotent Learned Image Compression with Right-Inverse
Yanghao Li · Tongda Xu · Yan Wang · Jingjing Liu · Ya-Qin Zhang
Bootstrapping Vision-Language Learning with Decoupled Language Pre-training
Yiren Jian · Chongyang Gao · Soroush Vosoughi
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models
Pum Jun Kim · Yoojin Jang · Jisu Kim · Jaejun Yoo
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation
Marco Bellagente · Manuel Brack · Hannah Teufel · Felix Friedrich · Björn Deiseroth · Constantin Eichenberg · Andrew Dai · Robert Baldock · Souradeep Nanda · Koen Oostermeijer · Andres Felipe Cruz-Salinas · Patrick Schramowski · Kristian Kersting · Samuel Weinbach
HeadSculpt: Crafting 3D Head Avatars with Text
Xiao Han · Yukang Cao · Kai Han · Xiatian Zhu · Jiankang Deng · Yi-Zhe Song · Tao Xiang · Kwan-Yee K. Wong
Training Energy-Based Normalizing Flow with Score-Matching Objectives
Chen-Hao Chao · Wei-Fang Sun · Yen-Chang Hsu · Zsolt Kira · Chun-Yi Lee
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment
Royi Rassin · Eran Hirsch · Daniel Glickman · Shauli Ravfogel · Yoav Goldberg · Gal Chechik
VideoComposer: Compositional Video Synthesis with Motion Controllability
Xiang Wang · Hangjie Yuan · Shiwei Zhang · Dayou Chen · Jiuniu Wang · Yingya Zhang · Yujun Shen · Deli Zhao · Jingren Zhou
Three Iterations of (d − 1)-WL Test Distinguish Non Isometric Clouds of d-dimensional Points
Valentino Delle Rose · Alexander Kozachinskiy · Cristobal Rojas · Mircea Petrache · Pablo Barceló
Graph Contrastive Learning with Stable and Scalable Spectral Encoding
Deyu Bo · Yuan Fang · Yang Liu · Chuan Shi
Reversible and irreversible bracket-based dynamics for deep graph neural networks
Anthony Gruber · Kookjin Lee · Nathaniel Trask
No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning
Zixing Song · Yifei Zhang · Irwin King
Implicit Convolutional Kernels for Steerable CNNs
Maksim Zhdanov · Nico Hoffmann · Gabriele Cesa
Learning Large Graph Property Prediction via Graph Segment Training
Kaidi Cao · Mangpo Phothilimthana · Sami Abu-El-Haija · Dustin Zelle · Yanqi Zhou · Charith Mendis · Jure Leskovec · Bryan Perozzi
Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding
George Ma · Yifei Wang · Yisen Wang
Re-Think and Re-Design Graph Neural Networks in Spaces of Continuous Graph Diffusion Functionals
Tingting Dan · Jiaqi Ding · Ziquan Wei · Shahar Kovalsky · Minjeong Kim · Won Hwa Kim · Guorong Wu
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs
Dingmin Wang · Yeyuan Chen
Recurrent Temporal Revision Graph Networks
Yizhou Chen · Anxiang Zeng · Qingtao Yu · Kerui Zhang · Cao Yuanpeng · Kangle Wu · Guangda Huzhang · Han Yu · Zhiming Zhou
Live Graph Lab: Towards Open, Dynamic and Real Transaction Graphs with NFT
Zhen Zhang · Bingqiao Luo · Shengliang Lu · Bingsheng He
V-InFoR: A Robust Graph Neural Networks Explainer for Structurally Corrupted Graphs
Senzhang Wang · Jun Yin · Chaozhuo Li · Xing Xie · Jianxin Wang
Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing
Jung Yeon Park · Lawson Wong · Robin Walters
LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
Ningyi Liao · Siqiang Luo · Xiang Li · Jieming Shi
Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition
Divin Yan · Gengchen Wei · Chen Yang · Shengzhong Zhang · zengfeng Huang
Universal Prompt Tuning for Graph Neural Networks
Taoran Fang · Yunchao Zhang · YANG YANG · Chunping Wang · Lei Chen
MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy
Honghua Dong · Jiawei Xu · Yu Yang · Rui Zhao · Shiwen Wu · Chun Yuan · Xiu Li · Chris Maddison · Lei Han
MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data
Tianyu Liu · Yuge Wang · Rex Ying · Hongyu Zhao
Learning Unseen Modality Interaction
Yunhua Zhang · Hazel Doughty · Cees Snoek
CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
Yulei Qin · Xingyu Chen · Yunhang Shen · Chaoyou Fu · Yun Gu · Ke Li · Xing Sun · Rongrong Ji
Rotating Features for Object Discovery
Sindy Löwe · Phillip Lippe · Francesco Locatello · Max Welling
CoLLAT: On Adding Fine-grained Audio Understanding to Language Models using Token-Level Locked-Language Tuning
Dadallage A R Silva · Spencer Whitehead · Christopher Lengerich · Hugh Leather
Topological Obstructions and How to Avoid Them
Babak Esmaeili · Robin Walters · Heiko Zimmermann · Jan-Willem van de Meent
Convolutional State Space Models for Long-Range Spatiotemporal Modeling
Jimmy Smith · Shalini De Mello · Jan Kautz · Scott Linderman · Wonmin Byeon
Evolving Connectivity for Recurrent Spiking Neural Networks
Guan Wang · Yuhao Sun · Sijie Cheng · Sen Song
Robust Learning with Progressive Data Expansion Against Spurious Correlation
Yihe Deng · Yu Yang · Baharan Mirzasoleiman · Quanquan Gu
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements
Gaurav Shrivastava · Gaurav Shrivastava · Ser Nam Lim · Abhinav Shrivastava
A Theory of Transfer-Based Black-Box Attacks: Explanation and Implications
Yanbo Chen · Weiwei Liu
Fantastic Robustness Measures: The Secrets of Robust Generalization
Hoki Kim · Jinseong Park · Yujin Choi · Jaewook Lee
Exploiting Connections between Lipschitz Structures for Certifiably Robust Deep Equilibrium Models
Aaron Havens · Alexandre Araujo · Siddharth Garg · Farshad Khorrami · Bin Hu
The Adversarial Consistency of Surrogate Risks for Binary Classification
Natalie Frank · Jonathan Niles-Weed
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness
Vivek Ramanujan · Thao Nguyen · Sewoong Oh · Ali Farhadi · Ludwig Schmidt
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
Elan Rosenfeld · Saurabh Garg
Hierarchical Randomized Smoothing
Yan Scholten · Jan Schuchardt · Aleksandar Bojchevski · Stephan Günnemann
Characterizing the Optimal $0-1$ Loss for Multi-class Classification with a Test-time Attacker
Sihui Dai · Wenxin Ding · Arjun Nitin Bhagoji · Daniel Cullina · Heather Zheng · Ben Zhao · Prateek Mittal
Optimal Transport Model Distributional Robustness
Van-Anh Nguyen · Trung Le · Anh Bui · Thanh-Toan Do · Dinh Phung
Effective Targeted Attacks for Adversarial Self-Supervised Learning
Minseon Kim · Hyeonjeong Ha · Sooel Son · Sung Ju Hwang
Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head
Alan Wang · Minh Nguyen · Mert Sabuncu
Cross-Scale MAE: A Tale of Multiscale Exploitation in Remote Sensing
Maofeng Tang · Andrei Cozma · Konstantinos Georgiou · Hairong Qi
Identifiable Contrastive Learning with Automatic Feature Importance Discovery
Qi Zhang · Yifei Wang · Yisen Wang
Test-time Training for Matching-based Video Object Segmentation
Juliette Bertrand · Giorgos Kordopatis Zilos · Yannis Kalantidis · Giorgos Tolias
Self-supervised Object-Centric Learning for Videos
Görkay Aydemir · Weidi Xie · Fatma Guney
No Representation Rules Them All in Category Discovery
Sagar Vaze · Andrea Vedaldi · Andrew Zisserman
To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis
Fuzhao Xue · Yao Fu · Wangchunshu Zhou · Zangwei Zheng · Zangwei Zheng · Yang You
Understanding Contrastive Learning via Distributionally Robust Optimization
Junkang Wu · Jiawei Chen · Jiancan Wu · Wentao Shi · Xiang Wang · Xiangnan He
Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression
Allan Raventós · Mansheej Paul · Feng Chen · Surya Ganguli
Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels
Zhen Liu · ma peitian · Dongliang Chen · Wenbin Pei · Qianli Ma
Change point detection and inference in multivariate non-parametric models under mixing conditions
Carlos Misael Madrid Padilla · Haotian Xu · Daren Wang · OSCAR HERNAN MADRID PADILLA · Yi Yu
Pairwise Causality Guided Transformers for Event Sequences
Xiao Shou · Debarun Bhattacharjya · Tian Gao · Dharmashankar Subramanian · Oktie Hassanzadeh · Kristin P Bennett
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
Sébastien Lachapelle · Divyat Mahajan · Ioannis Mitliagkas · Simon Lacoste-Julien
Globally injective and bijective neural operators
Takashi Furuya · Michael Puthawala · Matti Lassas · Maarten V. de Hoop
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement.
‪Yotam Alexander‬‏ · Nimrod De La Vega · Noam Razin · Nadav Cohen
Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs
Emmanuel Abbe · Elisabetta Cornacchia · Aryo Lotfi
The Exact Sample Complexity Gain from Invariances for Kernel Regression
Behrooz Tahmasebi · Stefanie Jegelka
Reliable learning in challenging environments
Maria-Florina Balcan · Steve Hanneke · Rattana Pukdee · Dravyansh Sharma
Representational Strengths and Limitations of Transformers
Clayton Sanford · Daniel Hsu · Matus Telgarsky · Matus Telgarsky
A General Theory of Correct, Incorrect, and Extrinsic Equivariance
Dian Wang · Xupeng Zhu · Jung Yeon Park · Mingxi Jia · Guanang Su · Robert Platt · Robin Walters
Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
Taiji Suzuki · Denny Wu · Atsushi Nitanda
Scaling Data-Constrained Language Models
Niklas Muennighoff · Alexander Rush · Boaz Barak · Teven Le Scao · Nouamane Tazi · Aleksandra Piktus · Sampo Pyysalo · Thomas Wolf · Colin Raffel
Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width
Dayal Singh Kalra · Maissam Barkeshli
Learning threshold neurons via edge of stability
Kwangjun Ahn · Sebastien Bubeck · Sinho Chewi · Yin Tat Lee · Felipe Suarez · Felipe Suarez · Yi Zhang
On student-teacher deviations in distillation: does it pay to disobey?
Vaishnavh Nagarajan · Aditya Menon · Srinadh Bhojanapalli · Hossein Mobahi · Sanjiv Kumar
Estimating Propensity for Causality-based Recommendation without Exposure Data
Zhongzhou Liu · Yuan Fang · Min Wu
Causal discovery from observational and interventional data across multiple environments
Adam Li · Amin Jaber · Elias Bareinboim
Global Optimality in Bivariate Gradient-based DAG Learning
Chang Deng · Kevin Bello · Pradeep Ravikumar · Bryon Aragam
A Cross-Moment Approach for Causal Effect Estimation
Yaroslav Kivva · Saber Salehkaleybar · Saber Salehkaleybar · Negar Kiyavash
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects
Ahmed Alaa · Zaid Ahmad · Mark van der Laan
Causal normalizing flows: from theory to practice
Adrián Javaloy · Pablo Sanchez-Martin · Isabel Valera
A Measure-Theoretic Axiomatisation of Causality
Junhyung Park · Simon Buchholz · Bernhard Schölkopf · Krikamol Muandet
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
Duligur Ibeling · Thomas Icard
Passive learning of active causal strategies in agents and language models
Andrew Lampinen · Stephanie Chan · Ishita Dasgupta · Andrew Nam · Jane Wang
Reusable Slotwise Mechanisms
Trang Nguyen · Amin Mansouri · Kanika Madan · Khuong Duy Nguyen · Kartik Ahuja · Dianbo Liu · Yoshua Bengio
Inner Product-based Neural Network Similarity
Wei Chen · Zichen Miao · Qiang Qiu
Loss Decoupling for Task-Agnostic Continual Learning
Yan-Shuo Liang · Wu-Jun Li
Beyond probability partitions: Calibrating neural networks with semantic aware grouping
Jia-Qi Yang · De-Chuan Zhan · Le Gan
Conformalized matrix completion
Yu Gui · Rina Barber · Cong Ma
Neuro-symbolic Learning Yielding Logical Constraints
Zenan Li · Yunpeng Huang · Zhaoyu Li · Yuan Yao · Jingwei Xu · Taolue Chen · Xiaoxing Ma · Jian Lu
Time-uniform confidence bands for the CDF under nonstationarity
Paul Mineiro · Steven Howard
Flow: Per-instance Personalized Federated Learning
Kunjal Panchal · Sunav Choudhary · Nisarg Parikh · Lijun Zhang · Hui Guan
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions
Samantha Chen · Yusu Wang
Diffusion Representation for Asymmetric Kernels via Magnetic Transform
Mingzhen He · FAN He · Ruikai Yang · Xiaolin Huang
Deep learning with kernels through RKHM and the Perron-Frobenius operator
Yuka Hashimoto · Masahiro Ikeda · Hachem Kadri
Learning Functional Transduction
Mathieu Chalvidal · Thomas Serre · Rufin VanRullen
Fast Approximation of Similarity Graphs with Kernel Density Estimation
Peter Macgregor · He Sun
Gradient-Free Kernel Stein Discrepancy
Matthew Fisher · Chris Oates
Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release
Yufan Li · Jialiang Mao · Iavor Bojinov
Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach
Yu-Hu Yan · Peng Zhao · Zhi-Hua Zhou
Active Bipartite Ranking
James Cheshire · Vincent Laurent · Stephan Clémençon
No-Regret Online Prediction with Strategic Experts
Omid Sadeghi · Maryam Fazel
PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis
Ali TehraniJamsaz · Quazi Ishtiaque Mahmud · Le Chen · Nesreen K. Ahmed · Ali Jannesari
Object-centric Learning with Cyclic Walks between Parts and Whole
Ziyu Wang · Mike Zheng Shou · Mengmi Zhang
Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures
David Loiseaux · Luis Scoccola · Mathieu Carrière · Magnus Bakke Botnan · Steve OUDOT
DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models
Tao Yang · Yuwang Wang · Yan Lu · Nanning Zheng
GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
Hao Zheng · Hui Lin · Rong Zhao
Learning Interpretable Low-dimensional Representation via Physical Symmetry
Xuanjie Liu · Daniel Chin · Yichen Huang · Gus Xia
SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning
Sarp Aykent · Tian Xia
Noether Embedding: Efficient Learning of Temporal Regularities
Chi Gao · Zidong Zhou · Luping Shi
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning
Yihua Zhang · Yimeng Zhang · Aochuan Chen · jinghan jia · Jiancheng Liu · Gaowen Liu · Mingyi Hong · Shiyu Chang · Sijia Liu
Improved Frequency Estimation Algorithms with and without Predictions
Anders Aamand · Justin Chen · Huy Nguyen · Sandeep Silwal · Ali Vakilian
Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds
Naoki Nishikawa · Yuichi Ike · Kenji Yamanishi
Foundation Model is Efficient Multimodal Multitask Model Selector
Fanqing Meng · Wenqi Shao · zhanglin peng · Chonghe Jiang · Kaipeng Zhang · Yu Qiao · Ping Luo
FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning
Dipam Goswami · Yuyang Liu · Bartłomiej Twardowski · Joost van de Weijer
Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration
Qi-Wei Wang · Da-Wei Zhou · Yi-Kai Zhang · De-Chuan Zhan · Han-Jia Ye
When Visual Prompt Tuning Meets Source-Free Domain Adaptive Semantic Segmentation
Xinhong Ma · Yiming Wang · Hao Liu · Tianyu Guo · Yunhe Wang
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective
Yuzheng Hu · Ruicheng Xian · Qilong Wu · Qiuling Fan · Lang Yin · Han Zhao
Retaining Beneficial Information from Detrimental Data for Neural Network Repair
Long-Kai Huang · Peilin Zhao · Junzhou Huang · Sinno Pan
A Theory of Multimodal Learning
Zhou Lu
Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale
Zhiwei Hao · Jianyuan Guo · Kai Han · Han Hu · Chang Xu · Yunhe Wang
One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation
Zhiwei Hao · Jianyuan Guo · Kai Han · Yehui Tang · Han Hu · Yunhe Wang · Chang Xu
ExPT: Synthetic Pretraining for Few-Shot Experimental Design
Tung Nguyen · Sudhanshu Agrawal · Aditya Grover
Neural Priming for Sample-Efficient Adaptation
Matthew Wallingford · Vivek Ramanujan · Alex Fang · Aditya Kusupati · Roozbeh Mottaghi · Aniruddha Kembhavi · Ludwig Schmidt · Ali Farhadi
Evolving Standardization for Continual Domain Generalization over Temporal Drift
Mixue Xie · Shuang Li · Longhui Yuan · Chi Liu · Zehui Dai
Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality
Liyuan Wang · Jingyi Xie · Xingxing Zhang · Mingyi Huang · Hang Su · Jun Zhu
Spuriosity Didn’t Kill the Classifier: Using Invariant Predictions to Harness Spurious Features
Cian Eastwood · Shashank Singh · Andrei L Nicolicioiu · Marin Vlastelica Pogančić · Julius von Kügelgen · Bernhard Schölkopf
Constant Approximation for Individual Preference Stable Clustering
Anders Aamand · Justin Chen · Allen Liu · Sandeep Silwal · Pattara Sukprasert · Ali Vakilian · Fred Zhang
Self-Adaptive Motion Tracking against On-body Displacement of Flexible Sensors
Chengxu Zuo · Fang Jiawei · Shihui Guo · Yipeng Qin
Differentiable Random Partition Models
Thomas Sutter · Alain Ryser · Joram Liebeskind · Julia Vogt
Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation
Jiachen Liang · RuiBing Hou · Hong Chang · Bingpeng MA · Shiguang Shan · Xilin Chen
Hierarchical clustering with dot products recovers hidden tree structure
Annie Gray · Alexander Modell · Patrick Rubin-Delanchy · Nick Whiteley
Multi-Object Representation Learning via Feature Connectivity and Object-Centric Regularization
Alex Foo · Wynne Hsu · Mong Li Lee
Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage
Yuheng Jia · Fuchao Yang · Yongqiang Dong
A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance
Bo Jiang · Ya-Feng Liu
Convex and Non-convex Optimization Under Generalized Smoothness
Haochuan Li · Jian Qian · Yi Tian · Alexander Rakhlin · Ali Jadbabaie
Federated Learning with Manifold Regularization and Normalized Update Reaggregation
Xuming An · Li Shen · Han Hu · Yong Luo
Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm
Jie Hao · Kaiyi Ji · Mingrui Liu
Exact Verification of ReLU Neural Control Barrier Functions
Hongchao Zhang · Junlin Wu · Yevgeniy Vorobeychik · Andrew Clark
Neural Lyapunov Control for Discrete-Time Systems
Junlin Wu · Andrew Clark · Yiannis Kantaros · Yevgeniy Vorobeychik
Revisiting Implicit Differentiation for Learning Problems in Optimal Control
Ming Xu · Timothy L. Molloy · Stephen Gould
ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
Ben Dai · Yixuan Qiu
Dynamic Non-monotone Submodular Maximization
Kiarash Banihashem · Leyla Biabani · Samira Goudarzi · MohammadTaghi Hajiaghayi · Peyman Jabbarzade · Morteza Monemizadeh
Energy-Efficient Scheduling with Predictions
Eric Balkanski · Noemie Perivier · Clifford Stein · Hao-Ting Wei
Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
Yuxin Pan · Yize Chen · Fangzhen Lin
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization
Darko Drakulic · Sofia Michel · Florian Mai · Arnaud Sors · Jean-Marc Andreoli
A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
Nathaniel Lahn · Sharath Raghvendra · Kaiyi Zhang
One-step differentiation of iterative algorithms
Jerome Bolte · Edouard Pauwels · Samuel Vaiter
Rethinking Gauss-Newton for learning over-parameterized models
Michael Arbel · Romain Menegaux · Pierre Wolinski
Many-body Approximation for Non-negative Tensors
KAZU GHALAMKARI · Mahito Sugiyama · Yoshinobu Kawahara
A Computationally Efficient Sparsified Online Newton Method
Fnu Devvrit · Sai Surya Duvvuri · Rohan Anil · Vineet Gupta · Cho-Jui Hsieh · Inderjit Dhillon
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
Yutong He · Xinmeng Huang · Kun Yuan
Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model
Alexander Tyurin · Peter Richtarik
Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection
Taehyeon Kim · Eric Lin · Junu Lee · Christian Lau · Vaikkunth Mugunthan
A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning
Ganyu Wang · Bin Gu · Qingsong Zhang · Xiang Li · Boyu Wang · Charles Ling
Finding Local Minima Efficiently in Decentralized Optimization
Wenhan Xian · Heng Huang
Momentum Provably Improves Error Feedback!
Ilyas Fatkhullin · Alexander Tyurin · Peter Richtarik
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
Hanhan Zhou · Tian Lan · Guru Prasadh Venkataramani · Wenbo Ding
Learning the Efficient Frontier
Philippe Chatigny · Ivan Sergienko · Ryan Ferguson · Jordan Weir · Maxime Bergeron
Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization
Jinbiao Chen · Jiahai Wang · Zizhen Zhang · Zhiguang Cao · Te Ye · Siyuan Chen
Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
Peiyao Xiao · Hao Ban · Hao Ban · Kaiyi Ji
Hypervolume Maximization: A Geometric View of Pareto Set Learning
Xiaoyuan Zhang · Xi Lin · Bo Xue · Yifan Chen · Qingfu Zhang
Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization
Taoli Zheng · Linglingzhi Zhu · Anthony Man-Cho So · Jose Blanchet · Jiajin Li
Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares
Christian Kümmerle · Christian Kümmerle · Johannes Maly
Outlier-Robust Gromov-Wasserstein for Graph Data
Lemin Kong · Jiajin Li · Jianheng Tang · Anthony Man-Cho So
Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints
Xinyi Hu · Jasper Lee · Jimmy Lee
DELTA: Diverse Client Sampling for Fasting Federated Learning
Lin Wang · Yongxin Guo · Tao Lin · Xiaoying Tang
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
Jiaxin Shi · Lester Mackey
Optimization and Bayes: A Trade-off for Overparameterized Neural Networks
Zhengmian Hu · Heng Huang
Unexpected Improvements to Expected Improvement for Bayesian Optimization
Sebastian Ament · Samuel Daulton · David Eriksson · Maximilian Balandat · Eytan Bakshy
Information Maximization Perspective of Orthogonal Matching Pursuit with Applications to Explainable AI
Aditya Chattopadhyay · Ryan Pilgrim · Rene Vidal
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval
Frederik Warburg · Marco Miani · Silas Brack · Søren Hauberg
Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
Tsai Hor Chan · Kin Wai Lau · Jiajun Shen · Guosheng Yin · Lequan Yu
Towards Accelerated Model Training via Bayesian Data Selection
Zhijie Deng · Peng Cui · Jun Zhu
Sparse Deep Learning for Time Series Data: Theory and Applications
Mingxuan Zhang · Yan Sun · Faming Liang
Undirected Probabilistic Model for Tensor Decomposition
Zerui Tao · Toshihisa Tanaka · Qibin Zhao
On Convergence of Polynomial Approximations to the Gaussian Mixture Entropy
Caleb Dahlke · Jason Pacheco
Bayesian Learning via Q-Exponential Process
Shuyi Li · Michael O'Connor · Shiwei Lan
Self-Consistent Velocity Matching of Probability Flows
Lingxiao Li · Samuel Hurault · Justin Solomon
Beyond Normal: On the Evaluation of Mutual Information Estimators
Paweł Czyż · Frederic Grabowski · Julia Vogt · Niko Beerenwinkel · Alexander Marx
The Behavior and Convergence of Local Bayesian Optimization
Kaiwen Wu · Kyurae Kim · Roman Garnett · Jacob Gardner
Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior
Luke Travis · Kolyan Ray
Survival Permanental Processes for Survival Analysis with Time-Varying Covariates
Hideaki Kim
Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity
Jian-Feng CAI · José Vinícius de Miranda Cardoso · Daniel Palomar · Jiaxi Ying
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
Neel Guha · Mayee Chen · Kush Bhatia · Azalia Mirhoseini · Frederic Sala · Christopher Ré
Unbiased learning of deep generative models with structured discrete representations
Henry C Bendekgey · Gabe Hope · Erik Sudderth
Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition
Xiwen WANG · Jiaxi Ying · Daniel Palomar
Langevin Quasi-Monte Carlo
Sifan Liu
Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk
Oren Mangoubi · Nisheeth K. Vishnoi
Differentiable and Stable Long-Range Tracking of Multiple Posterior Modes
Ali Younis · Erik Sudderth
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
Yeshu Li · Brian Ziebart
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow Shrink Trees
Bryan Andrews · Joseph Ramsey · Ruben Sanchez Romero · Jazmin Camchong · Erich Kummerfeld
NAS-X: Neural Adaptive Smoothing via Twisting
Dieterich Lawson · Michael Li · Scott Linderman
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent
Tianle Liu · Promit Ghosal · Krishnakumar Balasubramanian · Natesh Pillai
Compression with Bayesian Implicit Neural Representations
Zongyu Guo · Gergely Flamich · Jiajun He · Zhibo Chen · José Miguel Hernández-Lobato
Variational Inference with Gaussian Score Matching
Chirag Modi · Robert Gower · Charles Margossian · Yuling Yao · David Blei · Lawrence Saul
Imitation Learning from Vague Feedback
Xin-Qiang Cai · Yu-Jie Zhang · Chao-Kai Chiang · Masashi Sugiyama
Keep Various Trajectories: Promoting Exploration of Ensemble Policies in Continuous Control
Chao Li · Chen GONG · Qiang He · Xinwen Hou
Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric
Yiming Wang · Ming Yang · Renzhi Dong · Binbin Sun · Furui Liu · Leong Hou U
Structured State Space Models for In-Context Reinforcement Learning
Chris Lu · Yannick Schroecker · Albert Gu · Emilio Parisotto · Jakob Foerster · Satinder Singh · Feryal Behbahani
Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
Akhil Bagaria · Ben Abbatematteo · Omer Gottesman · Matt Corsaro · Sreehari Rammohan · George Konidaris
Finite-Time Analysis of Single-Timescale Actor-Critic
Xuyang Chen · Lin Zhao
Robust Knowledge Transfer in Tiered Reinforcement Learning
Jiawei Huang · Niao He
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions
Tiancheng Jin · Junyan Liu · Chloé Rouyer · William Chang · Chen-Yu Wei · Haipeng Luo
General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
Lingwei Zhu · Zheng Chen · Matthew Schlegel · Martha White
Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
Yangqing Fu · Ming Sun · Buqing Nie · Yue Gao
Multi-Modal Inverse Constrained Reinforcement Learning from a Mixture of Demonstrations
Guanren Qiao · Guiliang Liu · Pascal Poupart · Zhiqiang Xu
An Efficient End-to-End Training Approach for Zero-Shot Human-AI Coordination
Xue Yan · Jiaxian Guo · Xingzhou Lou · Jun Wang · Haifeng Zhang · Yali Du
Mutual Information Regularized Offline Reinforcement Learning
Xiao Ma · Bingyi Kang · Zhongwen Xu · Min Lin · Shuicheng Yan
Uncertainty-Aware Instance Reweighting for Off-Policy Learning
Xiaoying Zhang · Junpu Chen · Hongning Wang · Hong Xie · Yang Liu · John C.S. Lui · Hang Li
Efficient Diffusion Policies For Offline Reinforcement Learning
Bingyi Kang · Xiao Ma · Chao Du · Tianyu Pang · Shuicheng Yan
Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets
Anirudhan Badrinath · Yannis Flet-Berliac · Allen Nie · Emma Brunskill
A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories
Kai Yan · Alex Schwing · Yu-Xiong Wang
Adversarial Model for Offline Reinforcement Learning
Mohak Bhardwaj · Tengyang Xie · Byron Boots · Nan Jiang · Ching-An Cheng
Conservative State Value Estimation for Offline Reinforcement Learning
Liting Chen · Jie Yan · Zhengdao Shao · Lu Wang · Qingwei Lin · Saravanakumar Rajmohan · Thomas Moscibroda · Dongmei Zhang
Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning
Jianzhun Shao · Yun Qu · Chen Chen · Hongchang Zhang · Xiangyang Ji
Budgeting Counterfactual for Offline RL
Yao Liu · Yao Liu · Pratik Chaudhari · Rasool Fakoor
Explore to Generalize in Zero-Shot RL
Ev Zisselman · Itai Lavie · Daniel Soudry · Aviv Tamar
Regularity as Intrinsic Reward for Free Play
Cansu Sancaktar · Justus Piater · Georg Martius
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
Jialong Wu · Haoyu Ma · Chaoyi Deng · Mingsheng Long
Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
Dongyoung Kim · Jinwoo Shin · Pieter Abbeel · Younggyo Seo
Synthetic Experience Replay
Cong Lu · Philip Ball · Yee Whye Teh · Jack Parker-Holder
Resetting the Optimizer in Deep RL: An Empirical Study
Kavosh Asadi · Rasool Fakoor · Shoham Sabach
Learning to Discover Skills through Guidance
HYUNSEUNG KIM · BYUNG KUN LEE · Hojoon Lee · Dongyoon Hwang · Sejik Park · Kyushik Min · Jaegul Choo
Weakly Coupled Deep Q-Networks
Ibrahim El Shar · Daniel Jiang
Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
Jiahui Li · Kun Kuang · Baoxiang Wang · Xingchen Li · Fei Wu · Jun Xiao · Long Chen
Efficient Adversarial Attacks on Online Multi-agent Reinforcement Learning
Guanlin Liu · Lifeng LAI
Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning
Yifan Zang · Jinmin He · Kai Li · Haobo Fu · Qiang Fu · Junliang Xing · Jian Cheng
Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative MARL
Zhiwei Xu · Bin Zhang · dapeng li · Guangchong Zhou · Zeren Zhang · Guoliang Fan
Iteratively Learn Diverse Strategies with State Distance Information
Wei Fu · Weihua Du · Jingwei Li · Sunli Chen · Jingzhao Zhang · YI WU
Dynamic Regret of Adversarial Linear Mixture MDPs
Long-Fei Li · Peng Zhao · Zhi-Hua Zhou
Reference-Based POMDPs
Edward Kim · Yohan Karunanayake · Hanna Kurniawati
Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives
Wenjie Qiu · Wensen Mao · He Zhu
Diffused Task-Agnostic Milestone Planner
Mineui Hong · Minjae Kang · Songhwai Oh
Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning
Lin Guan · Karthik Valmeekam · Sarath Sreedharan · Subbarao Kambhampati
An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient
Yudong Luo · Guiliang Liu · Pascal Poupart · Yangchen Pan
Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
Zhuodong Yu · Ling Dai · Shaohang Xu · Siyang Gao · Chin Pang Ho
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models
Chudi Zhong · Zhi Chen · Jiachang Liu · Margo Seltzer · Cynthia Rudin
Post Hoc Explanations of Language Models Can Improve Language Models
Satyapriya Krishna · Jiaqi Ma · Dylan Slack · Asma Ghandeharioun · Sameer Singh · Himabindu Lakkaraju
When Does Optimizing a Proper Loss Yield Calibration?
Jaroslaw Blasiok · Parikshit Gopalan · Lunjia Hu · Preetum Nakkiran
In-Context Impersonation Reveals Large Language Models' Strengths and Biases
Leonard Salewski · Stephan Alaniz · Isabel Rio-Torto · Eric Schulz · Zeynep Akata · Zeynep Akata
HiBug: On Human-Interpretable Model Debug
Muxi Chen · YU LI · Qiang Xu
OKRidge: Scalable Optimal k-Sparse Ridge Regression
Jiachang Liu · Sam Rosen · Chudi Zhong · Cynthia Rudin
The Grand Illusion: The Myth of Software Portability and Implications for ML Progress.
Fraser Mince · Dzung Dinh · Jonas Kgomo · Neil Thompson · Sara Hooker
Explaining Predictive Uncertainty with Information Theoretic Shapley Values
David Watson · Joshua O'Hara · Niek Tax · Richard Mudd · Ido Guy
Towards Automated Circuit Discovery for Mechanistic Interpretability
Arthur Conmy · Augustine Mavor-Parker · Aengus Lynch · Stefan Heimersheim · Adrià Garriga-Alonso
Gaussian Process Probes (GPP) for Uncertainty-Aware Probing
Zi Wang · Alexander Ku · Jason Baldridge · Tom Griffiths · Been Kim
Learning to Receive Help: Intervention-Aware Concept Embedding Models
Mateo Espinosa Zarlenga · Katie Collins · Krishnamurthy Dvijotham · Adrian Weller · Zohreh Shams · Mateja Jamnik
Counterfactual Memorization in Neural Language Models
Chiyuan Zhang · Daphne Ippolito · Katherine Lee · Matthew Jagielski · Florian Tramer · Nicholas Carlini
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
Ryan Thompson · Amir Dezfouli · robert kohn
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective
Mathieu Serrurier · Franck Mamalet · Thomas FEL · Louis Béthune · Louis Béthune · Thibaut Boissin
Neural Sculpting: Uncovering hierarchically modular task structure in neural networks through pruning and network analysis
Shreyas Malakarjun Patil · Loizos Michael · Constantine Dovrolis
On the Relationship Between Relevance and Conflict in Online Social Link Recommendations
Yanbang Wang · Jon Kleinberg
Uncovering and Quantifying Social Biases in Code Generation
Yan Liu · Xiaokang Chen · Yan Gao · Zhe Su · Fengji Zhang · Daoguang Zan · Jian-Guang Lou · Pin-Yu Chen · Tsung-Yi Ho
Language Model Tokenizers Introduce Unfairness Between Languages
Aleksandar Petrov · Emanuele La Malfa · Philip Torr · Adel Bibi
Fairness Aware Counterfactuals for Subgroups
Loukas Kavouras · Konstantinos Tsopelas · Giorgos Giannopoulos · Dimitris Sacharidis · Eleni Psaroudaki · Nikolaos Theologitis · Dimitrios Rontogiannis · Dimitris Fotakis · Ioannis Emiris
Long-Term Fairness with Unknown Dynamics
Tongxin Yin · Reilly Raab · Mingyan Liu · Yang Liu
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Hammaad Adam · Fan Yin · Huibin Hu · Neil Tenenholtz · Lorin Crawford · Lester Mackey · Allison Koenecke
Bias in Evaluation Processes: An Optimization-Based Model
L. Elisa Celis · Amit Kumar · Anay Mehrotra · Nisheeth K. Vishnoi
Adapting Fairness Interventions to Missing Values
Raymond Feng · Flavio Calmon · Hao Wang
Differentially Private Statistical Inference through $\beta$-Divergence One Posterior Sampling
Jack Jewson · Sahra Ghalebikesabi · Chris C Holmes
UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition
Yuyuan Li · Chaochao Chen · Yizhao Zhang · Weiming Liu · Lingjuan Lyu · Xiaolin Zheng · Dan Meng · Jun Wang
Gaussian Membership Inference Privacy
Tobias Leemann · Martin Pawelczyk · Gjergji Kasneci
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation
Berivan Isik · Wei-Ning Chen · Ayfer Ozgur · Tsachy Weissman · Albert No
Privacy Auditing with One (1) Training Run
Thomas Steinke · Milad Nasr · Matthew Jagielski
k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy
Chenglin Fan · Ping Li · Xiaoyun Li
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
Jiaqi Liu · Jian Lou · Zhan Qin · Kui Ren
Bounding training data reconstruction in DP-SGD
Jamie Hayes · Borja Balle · Saeed Mahloujifar
DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning
Wenxuan Bao · Francesco Pittaluga · Vijay Kumar B G · Vincent Bindschaedler
On Computing Pairwise Statistics with Local Differential Privacy
Badih Ghazi · Pritish Kamath · Ravi Kumar · Pasin Manurangsi · Adam Sealfon
DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization
Hua Wang · Sheng Gao · Huanyu Zhang · Weijie Su · Milan Shen
Breaking the Communication-Privacy-Accuracy Tradeoff with $f$-Differential Privacy
Richeng Jin · Zhonggen Su · caijun zhong · Zhaoyang Zhang · Tony Quek · Huaiyu Dai
User-Level Differential Privacy With Few Examples Per User
Badih Ghazi · Pritish Kamath · Ravi Kumar · Pasin Manurangsi · Raghu Meka · Chiyuan Zhang
Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation
Palak Jain · Iden Kalemaj · Sofya Raskhodnikova · Satchit Sivakumar · Adam Smith
LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
Viraj Prabhu · Sriram Yenamandra · Sriram Yenamandra · Prithvijit Chattopadhyay · Judy Hoffman
Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
Alex Schlögl · Nora Hofer · Rainer Böhme
Boosting Adversarial Transferability by Achieving Flat Local Maxima
Zhijin Ge · Hongying Liu · Wang Xiaosen · Fanhua Shang · Yuanyuan Liu
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection
Sangha Park · Jisoo Mok · Dahuin Jung · Saehyung Lee · Sungroh Yoon
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
RENCHUNZI XIE · Hongxin Wei · Lei Feng · Yuzhou Cao · Bo An
Towards Stable Backdoor Purification through Feature Shift Tuning
Rui Min · Zeyu Qin · Li Shen · Minhao Cheng
Causal Fairness for Outcome Control
Drago Plecko · Elias Bareinboim
On the Exploitability of Instruction Tuning
Manli Shu · Jiongxiao Wang · Chen Zhu · Chen Zhu · Jonas Geiping · Chaowei Xiao · Tom Goldstein
Django: Detecting Trojans in Object Detection Models via Gaussian Focus Calibration
Guangyu Shen · Siyuan Cheng · Guanhong Tao · Kaiyuan Zhang · Yingqi Liu · Shengwei An · Shiqing Ma · Shiqing Ma · Xiangyu Zhang
A Unified Detection Framework for Inference-Stage Backdoor Defenses
Xun Xian · Ganghua Wang · Jayanth Srinivasa · Ashish Kundu · Xuan Bi · Mingyi Hong · Jie Ding
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots
Ruixiang (Ryan) Tang · Jiayi Yuan · Yiming Li · Zirui Liu · Rui Chen · Xia Hu
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources
Haotian Zheng · Qizhou Wang · Zhen Fang · Xiaobo Xia · Feng Liu · Tongliang Liu · Bo Han
Counterfactually Comparing Abstaining Classifiers
Yo Joong Choe · Aditya Gangrade · Aaditya Ramdas
Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training
Zhenyi Wang · Zhenyi Wang · Li Shen · Tongliang Liu · Tiehang Duan · Yanjun Zhu · Donglin Zhan · DAVID DOERMANN · Mingchen Gao
Private Everlasting Prediction
Moni Naor · Kobbi Nissim · Uri Stemmer · Chao Yan
On the Convergence of Encoder-only Shallow Transformers
Yongtao Wu · Fanghui Liu · Grigorios Chrysos · Volkan Cevher
A Competitive Algorithm for Agnostic Active Learning
Yihan Zhou · Eric Price
FIRAL: An Active Learning Algorithm for Multinomial Logistic Regression
Youguang Chen · George Biros
Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
Zhongqi Yue · QIANRU SUN · Hanwang Zhang
Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization
Aniket Murhekar · Zhuowen Yuan · Bhaskar Ray Chaudhury · Bo Li · Ruta Mehta
On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
Ioannis Anagnostides · Ioannis Panageas · Gabriele Farina · Tuomas Sandholm
Refined Mechanism Design for Approximately Structured Priors via Active Regression
Christos Boutsikas · Petros Drineas · Marios Mertzanidis · Alexandros Psomas · Paritosh Verma
Bicriteria Multidimensional Mechanism Design with Side Information
Siddharth Prasad · Maria-Florina Balcan · Tuomas Sandholm
Combinatorial Group Testing with Selfish Agents
Georgios Chionas · Dariusz Kowalski · Piotr Krysta
On the Last-iterate Convergence in Time-varying Zero-sum Games: Extra Gradient Succeeds where Optimism Fails
Yi Feng · Hu Fu · Qun Hu · Ping Li · Ioannis Panageas · bo peng · Xiao Wang
Exploiting hidden structures in non-convex games for convergence to Nash equilibrium
Iosif Sakos · Emmanouil-Vasileios Vlatakis-Gkaragkounis · Panayotis Mertikopoulos · Georgios Piliouras
Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback
Yang Cai · Haipeng Luo · Chen-Yu Wei · Weiqiang Zheng
No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand
Mengzi Amy Guo · Donghao Ying · Javad Lavaei · Zuo-Jun Shen
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games
Darshan Chakrabarti · Jelena Diakonikolas · Christian Kroer
Strategic Data Sharing between Competitors
Nikita Tsoy · Nikola Konstantinov
Strategic Classification under Unknown Personalized Manipulation
Han Shao · Avrim Blum · Omar Montasser
Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks
Hao-Kai Zhang · Chenghong Zhu · Mingrui Jing · Xin Wang
Generalized equivalences between subsampling and ridge regularization
Pratik Patil · Jin-Hong Du
Analyzing Generalization of Neural Networks through Loss Path Kernels
Yilan Chen · Wei Huang · Hao Wang · Charlotte Loh · Akash Srivastava · Lam Nguyen · Lily Weng
Adversarially Robust Learning with Uncertain Perturbation Sets
Tosca Lechner · Vinayak Pathak · Ruth Urner
PAC Learning Linear Thresholds from Label Proportions
Anand Brahmbhatt · Rishi Saket · Aravindan Raghuveer
Optimal Excess Risk Bounds for Empirical Risk Minimization on $p$-Norm Linear Regression
Ayoub El Hanchi · Murat Erdogdu
Learning via Wasserstein-Based High Probability Generalisation Bounds
Paul Viallard · Maxime Haddouche · Umut Simsekli · Benjamin Guedj
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
Lingjiong Zhu · Mert Gurbuzbalaban · Anant Raj · Umut Simsekli
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
Shuyao Li · Yu Cheng · Ilias Diakonikolas · Jelena Diakonikolas · Rong Ge · Stephen Wright
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression
Jing Xu · Jiaye Teng · Yang Yuan · Andrew Yao
On the Variance, Admissibility, and Stability of Empirical Risk Minimization
Gil Kur · Eli Putterman · Alexander Rakhlin
On Proper Learnability between Average- and Worst-case Robustness
Vinod Raman · UNIQUE SUBEDI · Ambuj Tewari
New Bounds for Hyperparameter Tuning of Regression Problems Across Instances
Maria-Florina Balcan · Anh Nguyen · Dravyansh Sharma
How many samples are needed to leverage smoothness?
Vivien Cabannes · Stefano Vigogna
The Pick-to-Learn Algorithm: Empowering Compression for Tight Generalization Bounds and Improved Post-training Performance
Dario Paccagnan · Marco Campi · Simone Garatti
Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization
Jun Chen · Hong Chen · Bin Gu · Hao Deng
A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time
Ranran Shen · Pan Peng
Hypothesis Selection with Memory Constraints
Maryam Aliakbarpour · Mark Bun · Adam Smith
Replicable Clustering
Hossein Esfandiari · Hossein Esfandiari · Amin Karbasi · Vahab Mirrokni · Grigoris Velegkas · Felix Zhou
Closing the Computational-Statistical Gap in Best Arm Identification for Combinatorial Semi-bandits
Ruo-Chun Tzeng · Po-An Wang · Alexandre Proutiere · Chi-Jen Lu
Statistical and Computational Trade-off in Multi-Agent Multi-Armed Bandits
Filippo Vannella · Alexandre Proutiere · Jaeseong Jeong
Efficient Online Clustering with Moving Costs
Dimitrios Christou · Stratis Skoulakis · Volkan Cevher
Double Auctions with Two-sided Bandit Feedback
Soumya Basu · Abishek Sankararaman
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits
Ruitu Xu · Yifei Min · Tianhao Wang
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
Kiarash Banihashem · MohammadTaghi Hajiaghayi · Suho Shin · Max Springer
Quantifying the Cost of Learning in Queueing Systems
Daniel Freund · Thodoris Lykouris · Wentao Weng
Multi-Agent Learning with Heterogeneous Linear Contextual Bandits
Anh Do · Thanh Nguyen-Tang · Raman Arora
Online Clustering of Bandits with Misspecified User Models
Zhiyong Wang · Jize Xie · Xutong Liu · Shuai Li · John C.S. Lui
Nearest Neighbour with Bandit Feedback
Stephen Pasteris · Chris Hicks · Vasilios Mavroudis
Incentivized Communication for Federated Bandits
Zhepei Wei · Chuanhao Li · Haifeng Xu · Hongning Wang
Cascading Contextual Assortment Bandits
Hyun-jun Choi · Rajan Udwani · Min-hwan Oh
Adaptive Selective Sampling for Online Prediction with Experts
Rui Castro · Fredrik Hellström · Tim van Erven
Robust Lipschitz Bandits to Adversarial Corruptions
Yue Kang · Cho-Jui Hsieh · Thomas Chun Man Lee
Improving the Knowledge Gradient Algorithm
Le Yang · Siyang Gao · Chin Pang Ho
Likelihood Ratio Confidence Sets for Sequential Decision Making
Nicolas Emmenegger · Mojmir Mutny · Andreas Krause
Optimal cross-learning for contextual bandits with unknown context distributions
Jon Schneider · Julian Zimmert
Non-Asymptotic Analysis of a UCB-based Top Two Algorithm
Marc Jourdan · Rémy Degenne
Online Ad Procurement in Non-stationary Autobidding Worlds
Jason Cheuk Nam Liang · Haihao Lu · Baoyu Zhou
Data-Dependent Bounds for Online Portfolio Selection Without Lipschitzness and Smoothness
Chung-En Tsai · Ying-Ting Lin · Yen-Huan Li
Riemannian Projection-free Online Learning
Zihao Hu · Guanghui Wang · Jacob Abernethy
Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing
Nived Rajaraman · Fnu Devvrit · Aryan Mokhtari · Kannan Ramchandran
AGD: an Auto-switchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix
Yun Yue · Zhiling Ye · Jiadi Jiang · Yongchao Liu · Ke Zhang
Nearly Tight Bounds For Differentially Private Multiway Cut
Mina Dalirrooyfard · Slobodan Mitrovic · Yuriy Nevmyvaka
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems
Junyi Li · Feihu Huang · Heng Huang
Embracing the chaos: analysis and diagnosis of numerical instability in variational flows
Zuheng Xu · Trevor Campbell
Attention as Implicit Structural Inference
Ryan Singh · Christopher L Buckley
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning
Ahmadreza Moradipari · Mohammad Pedramfar · Modjtaba Shokrian Zini · Vaneet Aggarwal
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration
Zhihan Liu · Miao Lu · WEI XIONG · Han Zhong · Hao Hu · Shenao Zhang · Sirui Zheng · Zhuoran Yang · Zhaoran Wang
Replicability in Reinforcement Learning
Amin Karbasi · Grigoris Velegkas · Lin Yang · Felix Zhou
Online Pricing for Multi-User Multi-Item Markets
Yigit Efe Erginbas · Thomas Courtade · Kannan Ramchandran · Soham Phade
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
Han Zhong · Tong Zhang
Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
Sharan Vaswani · Amirreza Kazemi · Reza Babanezhad Harikandeh · Nicolas Le Roux
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback
Yunchang Yang · Han Zhong · Tianhao Wu · Bin Liu · Liwei Wang · Simon Du
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
Hanlin Zhu · Paria Rashidinejad · Jiantao Jiao
Data-driven Optimal Filtering for Linear Systems with Unknown Noise Covariances
Shahriar Talebi · Amirhossein Taghvaei · Mehran Mesbahi
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient
Dylan J Foster · Noah Golowich · Jian Qian · Alexander Rakhlin · Ayush Sekhari
Generalized Logit Adjustment: Calibrating Fine-tuned Models by Removing Label Bias in Foundation Models
Beier Zhu · Kaihua Tang · QIANRU SUN · Hanwang Zhang
Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns
Xin Liu · Zheng Li · Yifan Gao · Jingfeng Yang · Jingfeng Yang · Tianyu Cao · Zhengyang Wang · Bing Yin · Yangqiu Song
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning
Xinyi Wang · Wanrong Zhu · Michael Saxon · Mark Steyvers · William Yang Wang
Common Ground in Cooperative Communication
Xiaoran Hao · Yash Jhaveri · Patrick Shafto
A Spectral Theory of Neural Prediction and Alignment
Abdulkadir Canatar · Abdulkadir Canatar · Jenelle Feather · Albert Wakhloo · SueYeon Chung
Language Models are Weak Learners
Hariharan Manikandan · Yiding Jiang · J. Zico Kolter
Any-to-Any Generation via Composable Diffusion
Zineng Tang · Ziyi Yang · Chenguang Zhu · Michael Zeng · Mohit Bansal
Group Robust Classification Without Any Group Information
Christos Tsirigotis · Joao Monteiro · Pau Rodriguez · David Vazquez · Aaron Courville
Structured Federated Learning through Clustered Additive Modeling
Jie Ma · Tianyi Zhou · Guodong Long · Jing Jiang · Chengqi Zhang
Robustness Guarantees for Adversarially Trained Neural Networks
Poorya Mianjy · Raman Arora
What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models
Khashayar Gatmiry · Zhiyuan Li · Tengyu Ma · Sashank Reddi · Stefanie Jegelka · Ching-Yao Chuang
A Diffusion-Model of Joint Interactive Navigation
Matthew Niedoba · Jonathan Lavington · Yunpeng Liu · Vasileios Lioutas · Justice Sefas · Xiaoxuan Liang · Dylan Green · Setareh Dabiri · Berend Zwartsenberg · Adam Scibior · Frank Wood
Cal-DETR: Calibrated Detection Transformer
Muhammad Akhtar Munir · Salman Khan · Muhammad Haris Khan · Mohsen Ali · Fahad Shahbaz Khan
Improving Graph Matching with Positional Reconstruction Encoder-Decoder Network
Yixiao Zhou · Ruiqi Jia · Hongxiang Lin · Hefeng Quan · Yumeng Zhao · Xiaoqing Lyu
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals
Tam Nguyen · Tan Nguyen · Richard Baraniuk
Collaborative Score Distillation for Consistent Visual Editing
Subin Kim · Kyungmin Lee · June Suk Choi · Jongheon Jeong · Kihyuk Sohn · Jinwoo Shin
A State Representation for Diminishing Rewards
Ted Moskovitz · Samo Hromadka · Ahmed Touati · Diana Borsa · Maneesh Sahani
SAMoSSA: Multivariate Singular Spectrum Analysis with Stochastic Autoregressive Noise
Abdullah Alomar · Munther Dahleh · Sean Mann · Devavrat Shah
Zero-shot causal learning
Hamed Nilforoshan · Michael Moor · Yusuf Roohani · Yining Chen · Anja Šurina · Michihiro Yasunaga · Sara Oblak · Jure Leskovec
Unsupervised Behavior Extraction via Random Intent Priors
Hao Hu · Yiqin Yang · Jianing Ye · Ziqing Mai · Chongjie Zhang
Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning
Cristina Menghini · Andrew Delworth · Stephen Bach
Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release
Abhishek Singh · Praneeth Vepakomma · Vivek Sharma · Ramesh Raskar
MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining
Jacob Portes · Alexander Trott · Sam Havens · DANIEL KING · Abhinav Venigalla · Moin Nadeem · Nikhil Sardana · Daya Khudia · Jonathan Frankle
Learning and Collusion in Multi-unit Auctions
Simina Branzei · Mahsa Derakhshan · Negin Golrezaei · Yanjun Han
Train 'n Trade: Foundations of Parameter Markets
Tzu-Heng Huang · Harit Vishwakarma · Frederic Sala
Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation
Mehrdad Ghadiri · David Arbour · Tung Mai · Cameron Musco · Anup B. Rao
Accelerated On-Device Forward Neural Network Training with Module-Wise Descending Asynchronism
Xiaohan Zhao · Hualin Zhang · Zhouyuan Huo · Bin Gu
PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference
Xutao Wang · Hanting Chen · Tianyu Guo · Yunhe Wang
FLSL: Feature-level Self-supervised Learning
Qing Su · Anton Netchaev · Hai Li · Shihao Ji
Convex-Concave Zero-Sum Markov Stackelberg Games
Denizalp Goktas · Arjun Prakash · Amy Greenwald
High Precision Causal Model Evaluation with Conditional Randomization
Chao Ma · Cheng Zhang
Single-Stage Visual Query Localization in Egocentric Videos
Hanwen Jiang · Santhosh Kumar Ramakrishnan · Kristen Grauman
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach
Haoxuan Li · Kunhan Wu · Chunyuan Zheng · Yanghao Xiao · Hao Wang · Zhi Geng · Fuli Feng · Xiangnan He · Peng Wu
Dynamic Sparsity Is Channel-Level Sparsity Learner
Lu Yin · Gen Li · Meng Fang · Li Shen · Tianjin Huang · Zhangyang "Atlas" Wang · Vlado Menkovski · Xiaolong Ma · Mykola Pechenizkiy · Shiwei Liu · Shiwei Liu
Adversarially Robust Distributed Count Tracking via Partial Differential Privacy
Zhongzheng Xiong · Xiaoyi Zhu · zengfeng Huang
Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations
Qingyao Sun · Kevin Murphy · Sayna Ebrahimi · Alexander D'Amour
Near-Optimal $k$-Clustering in the Sliding Window Model
David Woodruff · Peilin Zhong · Samson Zhou
Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance
Congyue Deng · Jiahui Lei · William B Shen · Kostas Daniilidis · Leonidas Guibas
Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations
Lifan Yuan · Yangyi Chen · Ganqu Cui · Hongcheng Gao · FangYuan Zou · Xingyi Cheng · Heng Ji · Zhiyuan Liu · Maosong Sun
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials
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