NeurIPS 2024 Schedule

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TUE 10 DEC

7:30 a.m.

Registration (East & West)

(ends 6:00 PM)

8 a.m.

Affinity Event:

Women in Machine Learning - Overflow Streaming

(ends 5:00 PM)

8:15 a.m.

Affinity Event:

Women in Machine Learning

(ends 5:00 PM)

8:30 a.m.

Expo Talk Panel:

AI for Autonomous Driving at Scale

(ends 9:30 AM)

Expo Talk Panel:

AI Verification & Validation: Trends, Applications, and Challenges

(ends 9:30 AM)

Expo Talk Panel:

Onboarding Generative AI at the Edge: Challenges and Solutions from Industrial Research

(ends 9:30 AM)

Expo Talk Panel:

Incentivizing Collaborative AI: A Decentralized Approach to Scaling Machine Learning

(ends 9:30 AM)

Expo Talk Panel:

Commerce Foundation Model

(ends 9:30 AM)

Expo Talk Panel:

TikTok Symphony: AIGC Solution for Advertising

(ends 9:30 AM)

Expo Talk Panel:

Core Technical Interpretation and Best Practices of Responsible AI

(ends 9:30 AM)

Expo Talk Panel:

Compute: Past, Present & Future

(ends 9:30 AM)

Affinity Event:

LatinX in AI

(ends 4:15 PM)

9 a.m.

Creative AI Session 1 [9:00-12:00]

Chairs: Jean Oh · Marcelo Coelho · Lia Coleman · Yingtao Tian

s 9:00-12:00

[9:00] Charting the Shapes of Stories with Game Theory

[9:00] Designed by a computer, built by a designer. Learnings from the fabrication of a chair generated by a ML model

[9:00] Exploratory Study Of Human-AI Interaction For Hindustani Music

[9:00] Forrest Dance

[9:00] Narratron: A Storytelling AI for Shadow Play

[9:00] OpenOpenAI and Alternate Altman: Democratizing the Future of AI through Speculative Participatory Media

[9:00] Pushing the Boundaries of AI Art: an Immodest Proposal

[9:00] Secure & Personalized Music-to-Video Generation via CHARCHA

[9:00] The Tale of Punyakoti: An AI-Enhanced Audio Experience

[9:00] Tuning Music Education: AI-Powered Personalization in learning music

[9:00] Typologies

(ends 12:00 PM)

Break:

Coffee Break

(ends 10:00 AM)

Streaming Hangout:

Streaming Hangout

(ends 5:00 PM)

Quiet Streaming Hangout:

Quiet Streaming Hangout

(ends 5:00 PM)

9:30 a.m.

Tutorial:

Causality for Large Language Models

(ends 12:00 PM)

Tutorial:

Watermarking for Large Language Models

(ends 12:00 PM)

Tutorial:

Evaluating Large Language Models - Principles, Approaches, and Applications

(ends 12:00 PM)

Tutorial:

Opening the Language Model Pipeline: A Tutorial on Data Preparation, Model Training, and Adaptation

(ends 12:00 PM)

Tutorial:

Dynamic Sparsity in Machine Learning: Routing Information through Neural Pathways

(ends 12:00 PM)

Tutorial:

Experimental Design and Analysis for AI Researchers

(ends 12:00 PM)

Tutorial:

Flow Matching for Generative Modeling

(ends 12:00 PM)

10 a.m.

Affinity Event:

Black in AI

(ends 5:00 PM)

Affinity Event:

Global South in AI

(ends 3:00 PM)

noon

Expo Workshop:

Active Training: Building Agentic Apps with Llama 3.2 and Llama Stack

(ends 1:30 PM)

Expo Workshop:

Accelerating Edge AI: Optimizing and Deploying AI Models with Qualcomm AI Hub

(ends 1:30 PM)

Expo Workshop:

Knowledge-enhanced LLMs for Industry Verticals

(ends 1:30 PM)

Expo Workshop:

Sony’s Efficient Content Creation and Editing through Deep Generative Models

(ends 1:30 PM)

Expo Workshop:

AutoGen 0.4: Redefining Agentic AI Systems

(ends 1:30 PM)

Expo Workshop:

Accelerating AI Research and Development with AMD Instinct Systems

(ends 1:30 PM)

Expo Workshop:

AutoGluon 1.2: Advancing AutoML with Foundational Models and LLM Agents

(ends 1:30 PM)

Expo Talk Panel:

Demystify Financial Textual Data with LLMs

(ends 1:00 PM)

Expo Workshop:

AI for Enhanced Spacecraft Orientation

(ends 1:30 PM)

Break:

Lunch (catered)

(ends 1:30 PM)

Exhibit Sponsor Hall:

Exhibit Sponsor Hall

(ends 8:00 PM)

1 p.m.

Creative AI Session 2 [1:00-4:00]

Chairs: Jean Oh · Marcelo Coelho · Lia Coleman · Yingtao Tian

s 1:00-4:00

[1:00] Charting the Shapes of Stories with Game Theory

[1:00] Designed by a computer, built by a designer. Learnings from the fabrication of a chair generated by a ML model

[1:00] Exploratory Study Of Human-AI Interaction For Hindustani Music

[1:00] Forrest Dance

[1:00] Narratron: A Storytelling AI for Shadow Play

[1:00] OpenOpenAI and Alternate Altman: Democratizing the Future of AI through Speculative Participatory Media

[1:00] Pushing the Boundaries of AI Art: an Immodest Proposal

[1:00] Secure & Personalized Music-to-Video Generation via CHARCHA

[1:00] The Tale of Punyakoti: An AI-Enhanced Audio Experience

[1:00] The Visual-Riddles Gallery: A Challenge of AI, Creativity and Ambiguity

[1:00] Tuning Music Education: AI-Powered Personalization in learning music

[1:00] Typologies

(ends 4:00 PM)

Affinity Event:

Muslims in ML

(ends 5:00 PM)

1:30 p.m.

Tutorial:

Beyond Decoding: Meta-Generation Algorithms for Large Language Models

(ends 4:00 PM)

Tutorial:

Out-of-Distribution Generalization: Shortcuts, Spuriousness, and Stability

(ends 4:00 PM)

Tutorial:

Generating Programmatic Solutions: Algorithms and Applications of Programmatic Reinforcement Learning and Code Generation

(ends 4:00 PM)

Tutorial:

Cross-disciplinary insights into alignment in humans and machines

(ends 4:00 PM)

Tutorial:

Advancing Data Selection for Foundation Models: From Heuristics to Principled Methods

(ends 4:00 PM)

Tutorial:

Sandbox for the Blackbox: How LLMs Learn Structured Data?

(ends 4:00 PM)

Tutorial:

PrivacyML: Meaningful Privacy-Preserving Machine Learning and How To Evaluate AI Privacy

(ends 4:00 PM)

1:45 p.m.

Affinity Event:

New in ML

(ends 6:00 PM)

2 p.m.

Mentorship:

Science Communication for AI Researchers: An Introduction

(ends 4:00 PM)

3 p.m.

Expo Demonstration:

Deploying Personal AI Assistants with Voice, LLMs, RAG via OpenVINO™ on the AI PC

(ends 5:00 PM)

Expo Demonstration:

MemoMagnet: A fridge-magnet memo agent based on LLM

(ends 5:00 PM)

Expo Demonstration:

HPC-AI.COM: Unleashing the Power of High-Performance Cloud Computing for Large-Scale AI Model Training

(ends 5:00 PM)

Expo Demonstration:

Augmenting Driving Scenes by High Fidelity Generative Models

(ends 5:00 PM)

Expo Demonstration:

Diffusion Video Editing on Mobile

(ends 5:00 PM)

Expo Demonstration:

Deploying Cached Conditional Mixture-of-Experts LLMs on Mobile Devices with Memory Constraints

(ends 5:00 PM)

Expo Demonstration:

Low-Rank Adaptation (LoRA) for Large Vision Model on a Mobile Device

(ends 5:00 PM)

Expo Demonstration:

Large Multimodal Model running on a mobile device

(ends 5:00 PM)

Expo Demonstration:

Open-Sora: Democratizing Efficient Video Production for All

(ends 5:00 PM)

Expo Demonstration:

Automatically Deploying a Sequence-to-Sequence Transformer for Accelerated Discovery on the IBM HERMES Project Chip

(ends 5:00 PM)

Expo Demonstration:

EvalAssist - An LLM-as-a-Judge Framework

(ends 5:00 PM)

Expo Demonstration:

Site Reliability Engineering Agent-101 for Incident Management

(ends 5:00 PM)

Expo Demonstration:

ProLLM: Program analysis driven, LLM assisted application modernization

(ends 5:00 PM)

Expo Demonstration:

IBM AI Agent SWE-1.0

(ends 5:00 PM)

Expo Demonstration:

Moving beyond chat: Enabling LLMs with intrinsic functions that give fine-grained control in application development

(ends 5:00 PM)

Expo Demonstration:

IBM Granite Vision Model for Enterprise AI

(ends 5:00 PM)

Expo Demonstration:

Trace: An LLM-powered End-to-end Optimization Framework of AI Workflow

(ends 5:00 PM)

Expo Demonstration:

Practices of Alibaba Cloud PAI (Platform for AI): An AI Native Large Models and AIGC Engineering Platform

(ends 5:00 PM)

4 p.m.

Expo Talk Panel:

Building industry-grade NLP applications for the financial domain

(ends 5:00 PM)

Expo Talk Panel:

Sequence Modeling in Financial Services

(ends 5:00 PM)

Expo Talk Panel:

Improving Foundation Models Using Human Data

(ends 5:00 PM)

Expo Talk Panel:

Colossal-AI: Breakthroughs in Efficient AI Training and Implementation

(ends 5:00 PM)

Expo Talk Panel:

AgentInstruct: Agentic flows are effective synthetic-data generators

(ends 5:00 PM)

Expo Talk Panel:

Granite Time Series Foundation Models

(ends 5:00 PM)

Expo Talk Panel:

Graph Reasoning in Large Language Models

(ends 5:00 PM)

Expo Talk Panel:

Training the Unprecedented Decart Diffusion World Simulator at scale on the Crusoe Cluster

(ends 5:00 PM)

Expo Talk Panel:

Symbolic AI and Foundation Models Integration towards Reliable and Trustworthy Industry-grade AI Systems

(ends 5:00 PM)

Break:

Coffee Break

(ends 4:30 PM)

5 p.m.

Remarks:

Opening Remarks

(ends 5:30 PM)

5:30 p.m.

Invited Talk:

The Golem vs. Stone Soup: Understanding How Children Learn Can Help Us Understand And Improve AI

Alison Gopnik

(ends 6:15 PM)

6:30 p.m.

Welcome Reception:

Welcome Reception

(ends 8:00 PM)

Affinity Poster Session:

Affinity Joint Poster Session

(ends 8:00 PM)

WED 11 DEC

7:30 a.m.

Registration (East & West)

(ends 6:00 PM)

Break:

Coffee Break

(ends 8:30 AM)

8:30 a.m.

Invited Talk:

Toward Industrial Artificial Intelligence

Sepp Hochreiter

(ends 9:30 AM)

9 a.m.

Exhibit Sponsor Hall:

Exhibit Sponsor Hall

(ends 5:00 PM)

Streaming Hangout:

Streaming Hangout

(ends 5:00 PM)

AI Hangout Room:

Quiet Streaming Hangout

(ends 5:00 PM)

9:30 a.m.

Break:

Coffee Break

(ends 10:00 AM)

10 a.m.

Oral Session 1A: Neuroscience and Intepretability [10:00-11:00]

Learning to grok: Emergence of in-context learning and skill composition in modular arithmetic tasks

Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes

NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction

(ends 11:00 AM)

Oral Session 1B: Human-AI Interaction [10:00-11:00]

Human Expertise in Algorithmic Prediction

RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation

The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models

(ends 11:00 AM)

Oral Session 1C: Optimization and Learning Theory [10:00-11:00]

The Road Less Scheduled

Learning diffusion at lightspeed

Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity

(ends 11:00 AM)

Oral Session 1D: Learning Theory [10:00-11:00]

Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure

Optimal Parallelization of Boosting

Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures

(ends 11:00 AM)

Affinity Event:

Queer in AI

(ends 5:00 PM)

Overflow for Oral Session 1D: Learning Theory [10:00-11:00]

(ends 11:00 AM)

Overflow for Oral Session 1C: Optimization and Learning Theory [10:00-11:00]

(ends 11:00 AM)

11 a.m.

Creative AI Session 3 [11:00-2:00]

Chairs: Jean Oh · Marcelo Coelho · Yingtao Tian · Lia Coleman

s 11:00-2:00

[11:00] AI Nüshu

[11:00] AI TrackMate: Finally, Someone Who Will Give Your Music More Than Just “Sounds Great!”

[11:00] Ambiguity in AI: The Paradox of Gender Neutrality

[11:00] break me, genAI

[11:00] Creative Loss: Ambiguity, Uncertainty and Indeterminacy

[11:00] Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance

[11:00] Learning to Move, Learning to Play, Learning to Animate

[11:00] Ørigin

[11:00] Perfect Syntax

[11:00] Redefining Artistic Boundaries: A Real-Time Interactive Painting Robot for Musicians

[11:00] Rhythm Bots: A Sensitive Improvisational Environment

[11:00] SketcherX: AI-Driven Interactive Robotic drawing with Diffusion model and Vectorization Techniques

[11:00] Sketchy Collections: Exploring Digital Museum Collections by Drawing via CLIP

[11:00] Tesseract.art, a real-time generative AI interactive painting robot for multidisciplinary art

[11:00] The Visual-Riddles Gallery: A Challenge of AI, Creativity and Ambiguity

[11:00] Towards a ‘Non-Universal‘ Architecture: Designing with Others through Gestures (1:1 Scale)

[11:00] Towards Kinetic Manipulation of the Latent Space

(ends 2:00 PM)

Poster Session 1 West [11:00-2:00]

Posters 11:00-2:00

Fast Proxy Experiment Design for Causal Effect Identification

DiffPhyCon: A Generative Approach to Control Complex Physical Systems

Sample Complexity of Interventional Causal Representation Learning

Mutli-Armed Bandits with Network Interference

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data

Linear Causal Representation Learning from Unknown Multi-node Interventions

Hybrid Top-Down Global Causal Discovery with Local Search for Linear and Nonlinear Additive Noise Models

Marginal Causal Flows for Validation and Inference

Benchmarking Counterfactual Image Generation

DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs

A Cross-Domain Benchmark for Active Learning

Comprehensive Framework for Curating Speech Datasets and Evaluating ASR Systems: A Case Study for the Polish Language

WildPPG: A Real-World PPG Dataset of Long Continuous Recordings

SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models

Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation

Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics

The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models

UltraEdit: Instruction-based Fine-Grained Image Editing at Scale

A Large-Scale Human-Centric Benchmark for Referring Expression Comprehension in the LMM Era

Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation

Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition

SHDocs: A dataset, benchmark, and method to efficiently generate high-quality, real-world specular highlight data with near-perfect alignment

GC-Bench: An Open and Unified Benchmark for Graph Condensation

Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification

Mitigating Object Hallucination via Concentric Causal Attention

MmCows: A Multimodal Dataset for Dairy Cattle Monitoring

Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

DetectEval: Benchmarking LLM-Generated Text Detection in Real-World Scenarios

VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding

Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration

CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset

Semi-Truths: A Large-Scale Dataset for Testing Robustness of AI-Generated Image Detectors

DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model

Game-Traversal-Benchmark: Evaluating Planning Abilities Of Large Language Models Via Traversing 2D Game Maps

DART-Eval: A Comprehensive DNA Language Model Evaluation Benchmark on Regulatory DNA

Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming

AllClear: A Comprehensive Dataset and Benchmark for Cloud Removal in Satellite Imagery

Multi-Chain Graphs of Graphs: A New Paradigm in Blockchain Dataset

Virtual Scanning: Unsupervised Non-line-of-sight Imaging from Irregularly Undersampled Transients

FinBen: An Holistic Financial Benchmark for Large Language Models

RedPajama: an Open Dataset for Training Large Language Models

CryoBench: Datasets and Benchmarks for Heterogeneous Cryo-EM Reconstruction

A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes

Advancing Video Anomaly Detection: A Concise Review and a New Dataset

Einsum Benchmark: Enabling the Development of Next-Generation Tensor Execution Engines

BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack

HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models

A Benchmark Suite for Evaluating Neural Mutual Information Estimators on Unstructured Datasets

MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations

Understanding Hallucinations in Diffusion Models through Mode Interpolation

SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents

Animal-Bench: Benchmarking Multimodal Video Models for Animal-centric Video Understanding

Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms

ABCFair: an Adaptable Benchmark approach for Comparing Fairness Methods

FairJob: A Real-World Dataset for Fairness in Online Systems

Harnessing Multiple Correlated Networks for Exact Community Recovery

Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma

OxonFair: A Flexible Toolkit for Algorithmic Fairness

Decision-Making Behavior Evaluation Framework for LLMs under Uncertain Context

Fair Secretaries with Unfair Predictions

Referring Human Pose and Mask Estimation In the Wild

Mitigating Spurious Correlations via Disagreement Probability

Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning

Perceptual Fairness in Image Restoration

Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks

Differentiable Quantum Computing for Large-scale Linear Control

Learning from Snapshots of Discrete and Continuous Data Streams

Active Classification with Few Queries under Misspecification

On the Comparison between Multi-modal and Single-modal Contrastive Learning

Statistical-Computational Trade-offs for Density Estimation

A two-scale Complexity Measure for Deep Learning Models

Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm

Active Learning of General Halfspaces: Label Queries vs Membership Queries

Group-wise oracle-efficient algorithms for online multi-group learning

Efficient Graph Matching for Correlated Stochastic Block Models

Efficiency for Free: Ideal Data Are Transportable Representations

No-Regret Learning for Fair Multi-Agent Social Welfare Optimization

Improved Analysis for Bandit Learning in Matching Markets

The Many Faces of Optimal Weak-to-Strong Learning

Information-theoretic Generalization Analysis for Expected Calibration Error

Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis

Exploring the Precise Dynamics of Single-Layer GAN Models: Leveraging Multi-Feature Discriminators for High-Dimensional Subspace Learning

Optimal Parallelization of Boosting

Distributed Least Squares in Small Space via Sketching and Bias Reduction

On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory

Strategic Littlestone Dimension: Improved Bounds on Online Strategic Classification

Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting

On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice

OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queries

No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting

Improved learning rates in multi-unit uniform price auctions

PRODuctive bandits: Importance Weighting No More

A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $\Theta(T^{2/3})$ and its Application to Best-of-Both-Worlds

Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis

Online Weighted Paging with Unknown Weights

Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization

Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients

BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning

Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation

Memory-Efficient LLM Training with Online Subspace Descent

Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements

SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization

Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Following

The Road Less Scheduled

Stochastic contextual bandits with graph feedback: from independence number to MAS number

F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning

Learning diffusion at lightspeed

Derivatives of Stochastic Gradient Descent in parametric optimization

Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem

Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors

Adaptive Proximal Gradient Method for Convex Optimization

A Simple and Optimal Approach for Universal Online Learning with Gradient Variations

Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions

A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem

Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations

Leveraging partial stragglers within gradient coding

LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing

SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead

Thinking Forward: Memory-Efficient Federated Finetuning of Language Models

The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize

Addressing Bias in Online Selection with Limited Budget of Comparisons

Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization

Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad

The Star Geometry of Critic-Based Regularizer Learning

Learning to Handle Complex Constraints for Vehicle Routing Problems

Rethinking the Capacity of Graph Neural Networks for Branching Strategy

IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs

pFedClub: Controllable Heterogeneous Model Aggregation for Personalized Federated Learning

Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity

Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting

Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization

Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs

No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation

Inversion-based Latent Bayesian Optimization

No-Regret Bandit Exploration based on Soft Tree Ensemble Model

Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry

Differentially Private Set Representations

Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification

Dual Critic Reinforcement Learning under Partial Observability

Real-Time Recurrent Learning using Trace Units in Reinforcement Learning

Distributional Preference Alignment of LLMs via Optimal Transport

A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data

Asynchronous Perception Machine for Efficient Test Time Training

Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning

Doubly Mild Generalization for Offline Reinforcement Learning

Worst-Case Offline Reinforcement Learning with Arbitrary Data Support

BECAUSE: Bilinear Causal Representation for Generalizable Offline Model-based Reinforcement Learning

Measuring Dejavu Memorization Efficiently

Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning

Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization

Time-Constrained Robust MDPs

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO

Mitigating Partial Observability in Decision Processes via the Lambda Discrepancy

Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL

Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning

Autoregressive Policy Optimization for Constrained Allocation Tasks

No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery

Diffusion-Reward Adversarial Imitation Learning

Reinforcement Learning Under Latent Dynamics: Toward Statistical and Algorithmic Modularity

Graph Learning for Numeric Planning

Towards Effective Planning Strategies for Dynamic Opinion Networks

Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration

Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents

MADiff: Offline Multi-agent Learning with Diffusion Models

Integrating Suboptimal Human Knowledge with Hierarchical Reinforcement Learning for Large-Scale Multiagent Systems

Opponent Modeling based on Subgoal Inference

DiffPO: A causal diffusion model for learning distributions of potential outcomes

SustainDC: Benchmarking for Sustainable Data Center Control

ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination

BenchMARL: Benchmarking Multi-Agent Reinforcement Learning

SPO: Sequential Monte Carlo Policy Optimisation

Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference

On the Complexity of Teaching a Family of Linear Behavior Cloning Learners

The Importance of Online Data: Understanding Preference Fine-tuning via Coverage

RA-PbRL: Provably Efficient Risk-Aware Preference-Based Reinforcement Learning

Robot Policy Learning with Temporal Optimal Transport Reward

LLM-based Skill Diffusion for Zero-shot Policy Adaptation

Stepwise Alignment for Constrained Language Model Policy Optimization

Regularized Conditional Diffusion Model for Multi-Task Preference Alignment

Beyond Optimism: Exploration With Partially Observable Rewards

Verified Safe Reinforcement Learning for Neural Network Dynamic Models

Is Score Matching Suitable for Estimating Point Processes?

Quantum algorithm for large-scale market equilibrium computation

Cross-Device Collaborative Test-Time Adaptation

Continuous Temporal Domain Generalization

Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning

Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice

Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity

Clustering with Non-adaptive Subset Queries

Partially Observable Cost-Aware Active-Learning with Large Language Models

On the Convergence of Loss and Uncertainty-based Active Learning Algorithms

Learnability Matters: Active Learning for Video Captioning

Online Bayesian Persuasion Without a Clue

Multi-Winner Reconfiguration

Conformalized Credal Set Predictors

Multi-Agent Coordination via Multi-Level Communication

Policy Optimization for Robust Average Reward MDPs

Offline Multitask Representation Learning for Reinforcement Learning

Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning

Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently

Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces

The Value of Reward Lookahead in Reinforcement Learning

Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces

CoFie: Learning Compact Neural Surface Representations with Coordinate Fields

Visual CoT: Advancing Multi-Modal Language Models with a Comprehensive Dataset and Benchmark for Chain-of-Thought Reasoning

A Careful Examination of Large Language Model Performance on Grade School Arithmetic

Text to Blind Motion

GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring

Euclidean distance compression via deep random features

Achieving Optimal Clustering in Gaussian Mixture Models with Anisotropic Covariance Structures

Breaking the curse of dimensionality in structured density estimation

Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models

Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm

AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases

Instance-adaptive Zero-shot Chain-of-Thought Prompting

Motion Graph Unleashed: A Novel Approach to Video Prediction

ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making

Vidu4D: Single Generated Video to High-Fidelity 4D Reconstruction with Dynamic Gaussian Surfels

Boosting Alignment for Post-Unlearning Text-to-Image Generative Models

Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification

Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning

TAPTRv2: Attention-based Position Update Improves Tracking Any Point

Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning

RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks

Can Simple Averaging Defeat Modern Watermarks?

Derivative-enhanced Deep Operator Network

Variational Flow Matching for Graph Generation

SpeechAlign: Aligning Speech Generation to Human Preferences

Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling

Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization

Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning

Rethinking Decoders for Transformer-based Semantic Segmentation: Compression is All You Need

LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling

SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network

Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset

SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion

PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher

Scaling Retrieval-Based Language Models with a Trillion-Token Datastore

Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure

Implicit Curriculum in Procgen Made Explicit

Wings: Learning Multimodal LLMs without Text-only Forgetting

One-Step Diffusion Distillation through Score Implicit Matching

Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion

Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning

Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness

DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning

Optimal Algorithms for Online Convex Optimization with Adversarial Constraints

PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation

Diffusion Actor-Critic with Entropy Regulator

Simplified and Generalized Masked Diffusion for Discrete Data

Iterative Methods via Locally Evolving Set Process

AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies

(ends 2:00 PM)

Poster Session 1 East [11:00-2:00]

Posters 11:00-2:00

SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering

GFlowNet Assisted Biological Sequence Editing

How Does Message Passing Improve Collaborative Filtering?

MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI

Coupled Mamba: Enhanced Multimodal Fusion with Coupled State Space Model

Information Re-Organization Improves Reasoning in Large Language Models

Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification

Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation

NeuralSteiner: Learning Steiner Tree for Overflow-avoiding Global Routing in Chip Design

PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition

LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation

GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning

HEST-1k: A Dataset For Spatial Transcriptomics and Histology Image Analysis

Molecule Generation with Fragment Retrieval Augmentation

Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis

Approximating mutual information of high-dimensional variables using learned representations

A probability contrastive learning framework for 3D molecular representation learning

Full-Atom Peptide Design with Geometric Latent Diffusion

How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval

Cluster-wise Graph Transformer with Dual-granularity Kernelized Attention

Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models

Adaptive Visual Scene Understanding: Incremental Scene Graph Generation

DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation

Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering for HDR View Synthesis

MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting

LION: Linear Group RNN for 3D Object Detection in Point Clouds

LaSe-E2V: Towards Language-guided Semantic-aware Event-to-Video Reconstruction

3D Focusing-and-Matching Network for Multi-Instance Point Cloud Registration

MutaPLM: Protein Language Modeling for Mutation Explanation and Engineering

Generative Modeling of Molecular Dynamics Trajectories

DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM

Kermut: Composite kernel regression for protein variant effects

Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design

M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and RGB Data

Memorize What Matters: Emergent Scene Decomposition from Multitraverse

Consensus Learning with Deep Sets for Essential Matrix Estimation

UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-Classes

Exploring Context Window of Large Language Models via Decomposed Positional Vectors

2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution

Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation

Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting

NVRC: Neural Video Representation Compression

Real-world Image Dehazing with Coherence-based Pseudo Labeling and Cooperative Unfolding Network

DMesh: A Differentiable Mesh Representation

Where's Waldo: Diffusion Features For Personalized Segmentation and Retrieval

Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf

Exploiting Descriptive Completeness Prior for Cross Modal Hashing with Incomplete Labels

Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning

Transformer Doctor: Diagnosing and Treating Vision Transformers

Soft Superpixel Neighborhood Attention

VQ-Map: Bird's-Eye-View Map Layout Estimation in Tokenized Discrete Space via Vector Quantization

Rejection via Learning Density Ratios

AverNet: All-in-one Video Restoration for Time-varying Unknown Degradations

3D Gaussian Splatting as Markov Chain Monte Carlo

VeXKD: The Versatile Integration of Cross-Modal Fusion and Knowledge Distillation for 3D Perception

EZ-HOI: VLM Adaptation via Guided Prompt Learning for Zero-Shot HOI Detection

Equivariant spatio-hemispherical networks for diffusion MRI deconvolution

Estimating Ego-Body Pose from Doubly Sparse Egocentric Video Data

Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection

Multi-Object 3D Grounding with Dynamic Modules and Language-Informed Spatial Attention

Towards Croppable Implicit Neural Representations

FreeSplat: Generalizable 3D Gaussian Splatting Towards Free View Synthesis of Indoor Scenes

Linear Uncertainty Quantification of Graphical Model Inference

MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution

GSDF: 3DGS Meets SDF for Improved Neural Rendering and Reconstruction

Beware of Road Markings: A New Adversarial Patch Attack to Monocular Depth Estimation

LiT: Unifying LiDAR "Languages" with LiDAR Translator

Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis

ReGS: Reference-based Controllable Scene Stylization with Gaussian Splatting

Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation

Zero-shot Image Editing with Reference Imitation

DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation

SHMT: Self-supervised Hierarchical Makeup Transfer via Latent Diffusion Models

UDPM: Upsampling Diffusion Probabilistic Models

Rethinking The Training And Evaluation of Rich-Context Layout-to-Image Generation

Unlocking the Capabilities of Masked Generative Models for Image Synthesis via Self-Guidance

Learning Action and Reasoning-Centric Image Editing from Videos and Simulation

START: A Generalized State Space Model with Saliency-Driven Token-Aware Transformation

AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation

Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition

Reproducibility study of “LICO: Explainable Models with Language-Image Consistency"

SeeClear: Semantic Distillation Enhances Pixel Condensation for Video Super-Resolution

FashionR2R: Texture-preserving Rendered-to-Real Image Translation with Diffusion Models

pcaGAN: Improving Posterior-Sampling cGANs via Principal Component Regularization

IF-Font: Ideographic Description Sequence-Following Font Generation

ReFIR: Grounding Large Restoration Models with Retrieval Augmentation

HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach

Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation

OMG-LLaVA: Bridging Image-level, Object-level, Pixel-level Reasoning and Understanding

One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos

Automated Label Unification for Multi-Dataset Semantic Segmentation with GNNs

LESS: Label-Efficient and Single-Stage Referring 3D Segmentation

Towards Flexible Visual Relationship Segmentation

ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

ActAnywhere: Subject-Aware Video Background Generation

NaRCan: Natural Refined Canonical Image with Integration of Diffusion Prior for Video Editing

Collaborative Video Diffusion: Consistent Multi-video Generation with Camera Control

4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models

COVE: Unleashing the Diffusion Feature Correspondence for Consistent Video Editing

X-Ray: A Sequential 3D Representation For Generation

MotionBooth: Motion-Aware Customized Text-to-Video Generation

LRM-Zero: Training Large Reconstruction Models with Synthesized Data

XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation

A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation

AdaPKC: PeakConv with Adaptive Peak Receptive Field for Radar Semantic Segmentation

E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding

A Motion-aware Spatio-temporal Graph for Video Salient Object Ranking

Towards Multi-Domain Learning for Generalizable Video Anomaly Detection

No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance

REDUCR: Robust Data Downsampling using Class Priority Reweighting

Data Acquisition via Experimental Design for Data Markets

Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts

TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models

Algorithmic progress in language models

Optimal and Approximate Adaptive Stochastic Quantization

Improving robustness to corruptions with multiplicative weight perturbations

Credal Deep Ensembles for Uncertainty Quantification

Understanding the Differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks

Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers

Single Image Reflection Separation via Dual-Stream Interactive Transformers

Infinite-Dimensional Feature Interaction

DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation

3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability

A Layer-Wise Natural Gradient Optimizer for Training Deep Neural Networks

Neglected Hessian component explains mysteries in sharpness regularization

Learning 3D Equivariant Implicit Function with Patch-Level Pose-Invariant Representation

Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations

Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers

Spectral Adapter: Fine-Tuning in Spectral Space

Linear Transformers are Versatile In-Context Learners

KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization

Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models

Learning symmetries via weight-sharing with doubly stochastic tensors

Bootstrapping Top-down Information for Self-modulating Slot Attention

Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning

Preventing Model Collapse in Deep Canonical Correlation Analysis by Noise Regularization

Algebraic Positional Encodings

TripletCLIP: Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives

VMamba: Visual State Space Model

Decoupled Kullback-Leibler Divergence Loss

SAM-Guided Masked Token Prediction for 3D Scene Understanding

Constructing Semantics-Aware Adversarial Examples with Probabilistic Perspective

Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models

Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing

Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences

Scalable Neural Network Verification with Branch-and-bound Inferred Cutting Planes

Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?

Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework

A teacher-teacher framework for clinical language representation learning

Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning

Understanding Transformer Reasoning Capabilities via Graph Algorithms

Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings

How does Gradient Descent Learn Features --- A Local Analysis for Regularized Two-Layer Neural Networks

Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization

GACL: Exemplar-Free Generalized Analytic Continual Learning

Transformers are Minimax Optimal Nonparametric In-Context Learners

On the Saturation Effects of Spectral Algorithms in Large Dimensions

Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks

Watch Out for Your Agents! Investigating Backdoor Threats to LLM-Based Agents

Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame

What makes unlearning hard and what to do about it

Toward a Well-Calibrated Discrimination via Survival Outcome-Aware Contrastive Learning

ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification

Categorical Flow Matching on Statistical Manifolds

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation

Stress-Testing Capability Elicitation With Password-Locked Models

Hierarchical Selective Classification

Learning Infinitesimal Generators of Continuous Symmetries from Data

AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks

SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform

CODA: A Correlation-Oriented Disentanglement and Augmentation Modeling Scheme for Better Resisting Subpopulation Shifts

Spiking Token Mixer: A event-driven friendly Former structure for spiking neural networks

Acoustic Volume Rendering for Neural Impulse Response Fields

SceneCraft: Layout-Guided 3D Scene Generation

Towards a Scalable Reference-Free Evaluation of Generative Models

Image Reconstruction Via Autoencoding Sequential Deep Image Prior

B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory

Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models

A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health

Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics

Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences

Synergistic Dual Spatial-aware Generation of Image-to-text and Text-to-image

ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation

Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences

Classification Diffusion Models: Revitalizing Density Ratio Estimation

Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation

Evaluating the design space of diffusion-based generative models

Learning Diffusion Priors from Observations by Expectation Maximization

DiffGS: Functional Gaussian Splatting Diffusion

A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective

SyncTweedies: A General Generative Framework Based on Synchronized Diffusions

VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models

Local Curvature Smoothing with Stein's Identity for Efficient Score Matching

Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces

Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference

DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection

Theoretical guarantees in KL for Diffusion Flow Matching

Generative Fractional Diffusion Models

Model-based Diffusion for Trajectory Optimization

Constrained Diffusion Models via Dual Training

Diffusion of Thought: Chain-of-Thought Reasoning in Diffusion Language Models

Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems

Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual Noise

DiffuPac: Contextual Mimicry in Adversarial Packets Generation via Diffusion Model

Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models

Neural Residual Diffusion Models for Deep Scalable Vision Generation

Taming Generative Diffusion Prior for Universal Blind Image Restoration

Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models

Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training

Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens

Where does In-context Learning \\ Happen in Large Language Models?

Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack

Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising

Coherent 3D Scene Diffusion From a Single RGB Image

PrefPaint: Aligning Image Inpainting Diffusion Model with Human Preference

Attack-Resilient Image Watermarking Using Stable Diffusion

Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning

Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure

Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models

4Diffusion: Multi-view Video Diffusion Model for 4D Generation

ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization

AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents

From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When

Accuracy is Not All You Need

Efficient Contextual LLM Cascades through Budget-Constrained Policy Learning

Verified Code Transpilation with LLMs

Piecewise deterministic generative models

On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution

Can LLMs Solve Molecule Puzzles? A Multimodal Benchmark for Molecular Structure Elucidation

Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning

Multi-language Diversity Benefits Autoformalization

SemCoder: Training Code Language Models with Comprehensive Semantics Reasoning

Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees

What do Graph Neural Networks learn? Insights from Tropical Geometry

Graphcode: Learning from multiparameter persistent homology using graph neural networks

Deep Homomorphism Networks

Spectral Graph Pruning Against Over-Squashing and Over-Smoothing

RAGraph: A General Retrieval-Augmented Graph Learning Framework

EGonc : Energy-based Open-Set Node Classification with substitute Unknowns

Graph Neural Networks and Arithmetic Circuits

[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks

[Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework"

DAPE: Data-Adaptive Positional Encoding for Length Extrapolation

Chain of Thoughtlessness? An Analysis of CoT in Planning

AutoPSV: Automated Process-Supervised Verifier

Are Graph Neural Networks Optimal Approximation Algorithms?

State Space Models on Temporal Graphs: A First-Principles Study

Mixture of Link Predictors on Graphs

DiGRAF: Diffeomorphic Graph-Adaptive Activation Function

The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks

Logical characterizations of recurrent graph neural networks with reals and floats

Rethinking Reconstruction-based Graph-Level Anomaly Detection: Limitations and a Simple Remedy

GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules

Unitary Convolutions for Learning on Graphs and Groups

Online Relational Inference for Evolving Multi-agent Interacting Systems

Graph Neural Networks Do Not Always Oversmooth

Microstructures and Accuracy of Graph Recall by Large Language Models

Initialization is Critical to Whether Transformers Fit Composite Functions by Reasoning or Memorizing

Great Minds Think Alike: The Universal Convergence Trend of Input Salience

Conditional Density Estimation with Histogram Trees

LLM Circuit Analyses Are Consistent Across Training and Scale

DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models

Towards Human-AI Complementarity with Prediction Sets

Human Expertise in Algorithmic Prediction

RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation

Generative Semi-supervised Graph Anomaly Detection

Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval

Denoising Diffusion Path: Attribution Noise Reduction with An Auxiliary Diffusion Model

Selective Explanations

Interpretable Image Classification with Adaptive Prototype-based Vision Transformers

The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models

Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks

Refusal in Language Models Is Mediated by a Single Direction

Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling

SafeWorld: Geo-Diverse Safety Alignment

Weak-eval-Strong: Evaluating and Eliciting Lateral Thinking of LLMs with Situation Puzzles

Semantics and Spatiality of Emergent Communication

Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum

Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers

LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search

Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation

Separate and Reconstruct: Asymmetric Encoder-Decoder for Speech Separation

Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction

Aligning to Thousands of Preferences via System Message Generalization

ContextCite: Attributing Model Generation to Context

To Believe or Not to Believe Your LLM: IterativePrompting for Estimating Epistemic Uncertainty

LLM-Check: Investigating Detection of Hallucinations in Large Language Models

Large language model validity via enhanced conformal prediction methods

Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies

Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data

Scalable DBSCAN with Random Projections

Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices

Diffeomorphic interpolation for efficient persistence-based topological optimization

Supervised Kernel Thinning

Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval

Neuronal Competition Groups with Supervised STDP for Spike-Based Classification

Quantifying the Gain in Weak-to-Strong Generalization

Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning

Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging

A Metalearned Neural Circuit for Nonparametric Bayesian Inference

Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion

NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples

Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection

(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning

QBB: Quantization with Binary Bases for LLMs

On the cohesion and separability of average-link for hierarchical agglomerative clustering

Boosting Transferability and Discriminability for Time Series Domain Adaptation

$\textit{Trans-LoRA}$: towards data-free Transferable Parameter Efficient Finetuning

Learning from Offline Foundation Features with Tensor Augmentations

Learning Where to Edit Vision Transformers

Zero-Shot Transfer of Neural ODEs

DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity

SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers

MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learning

Probabilistic Conformal Distillation for Enhancing Missing Modality Robustness

Artemis: Towards Referential Understanding in Complex Videos

HEALNet: Multimodal Fusion for Heterogeneous Biomedical Data

Dense Connector for MLLMs

SpatialRGPT: Grounded Spatial Reasoning in Vision-Language Models

Visual Perception by Large Language Model’s Weights

Accelerating Pre-training of Multimodal LLMs via Chain-of-Sight

Why are Visually-Grounded Language Models Bad at Image Classification?

Continual Audio-Visual Sound Separation

RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions

HAWK: Learning to Understand Open-World Video Anomalies

Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers

Empowering Visible-Infrared Person Re-Identification with Large Foundation Models

What matters when building vision-language models?

MoMu-Diffusion: On Learning Long-Term Motion-Music Synchronization and Correspondence

Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning

Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning

Leveraging Visual Tokens for Extended Text Contexts in Multi-Modal Learning

No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models

What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights

A Sober Look at the Robustness of CLIPs to Spurious Features

Automated Multi-level Preference for MLLMs

Unified Lexical Representation for Interpretable Visual-Language Alignment

Deep Correlated Prompting for Visual Recognition with Missing Modalities

Evaluating alignment between humans and neural network representations in image-based learning tasks

NeuroClips: Towards High-fidelity and Smooth fMRI-to-Video Reconstruction

Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems

Flexible task abstractions emerge in linear networks with fast and bounded units

Inferring stochastic low-rank recurrent neural networks from neural data

Latent Learning Progress Drives Autonomous Goal Selection in Human Reinforcement Learning

LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model

Trading Place for Space: Increasing Location Resolution Reduces Contextual Capacity in Hippocampal Codes

Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment

Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks

Learning Cortico-Muscular Dependence through Orthonormal Decomposition of Density Ratios

Symbolic Regression with a Learned Concept Library

Active design of two-photon holographic stimulation for identifying neural population dynamics

Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models

Flexible mapping of abstract domains by grid cells via self-supervised extraction and projection of generalized velocity signals

Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking

To Learn or Not to Learn, That is the Question — A Feature-Task Dual Learning Model of Perceptual Learning

Compositional Generalization Across Distributional Shifts with Sparse Tree Operations

Latent Diffusion for Neural Spiking Data

Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces

Multiple Physics Pretraining for Spatiotemporal Surrogate Models

Poseidon: Efficient Foundation Models for PDEs

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs

Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling

Validating Climate Models with Spherical Convolutional Wasserstein Distance

Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks

A Recipe for Charge Density Prediction

Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing

Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees

Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood

Preferential Normalizing Flows

Trajectory Diffusion for ObjectGoal Navigation

Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning

Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk

Physics-Informed Variational State-Space Gaussian Processes

Nonstationary Sparse Spectral Permanental Process

Pre-trained Gaussian Processes for Bayesian Optimization

Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA

Bayesian Adaptive Calibration and Optimal Design

Probabilistic size-and-shape functional mixed models

Conjugate Bayesian Two-step Change Point Detection for Hawkes Process

High Rank Path Development: an approach to learning the filtration of stochastic processes

EASI: Evolutionary Adversarial Simulator Identification for Sim-to-Real Transfer

Reasoning Multi-Agent Behavioral Topology for Interactive Autonomous Driving

Variational Distillation of Diffusion Policies into Mixture of Experts

DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection

ANT: Adaptive Noise Schedule for Time Series Diffusion Models

Scaling Law for Time Series Forecasting

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables

Conformalized Time Series with Semantic Features

Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification

Studying How to Efficiently and Effectively Guide Models with Explanations - A Reproducibility Study

An Analysis of Robustness of Non-Lipschitz Networks

Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents

Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models

Training for Stable Explanation for Free

Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models

Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation

Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously

ZeroMark: Towards Dataset Ownership Verification without Disclosing Watermark

Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack

The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection

Improved Generation of Adversarial Examples Against Safety-aligned LLMs

Federated Model Heterogeneous Matryoshka Representation Learning

Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection

Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models

Beyond Slow Signs in High-fidelity Model Extraction

Controlling Counterfactual Harm in Decision Support Systems Based on Prediction Sets

LACIE: Listener-Aware Finetuning for Calibration in Large Language Models

RaVL: Discovering and Mitigating Spurious Correlations in Fine-Tuned Vision-Language Models

Weak Supervision Performance Evaluation via Partial Identification

Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients

When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback

Optimistic Verifiable Training by Controlling Hardware Nondeterminism

Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models

Neural Model Checking

Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement

NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation

Improved Few-Shot Jailbreaking Can Circumvent Aligned Language Models and Their Defenses

From Trojan Horses to Castle Walls: Unveiling Bilateral Data Poisoning Effects in Diffusion Models

Bridging OOD Detection and Generalization: A Graph-Theoretic View

Pseudo-Private Data Guided Model Inversion Attacks

Dual-Personalizing Adapter for Federated Foundation Models

Vaccine: Perturbation-aware Alignment for Large Language Models against Harmful Fine-tuning Attack

Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models

Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity

Confidence Calibration of Classifiers with Many Classes

Large Language Model Unlearning via Embedding-Corrupted Prompts

$\texttt{ConflictBank}$: A Benchmark for Evaluating the Influence of Knowledge Conflicts in LLMs

GS-Hider: Hiding Messages into 3D Gaussian Splatting

Linear Regression using Heterogeneous Data Batches

DiTFastAttn: Attention Compression for Diffusion Transformer Models

Stratified Prediction-Powered Inference for Effective Hybrid Evaluation of Language Models

Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD

Any2Policy: Learning Visuomotor Policy with Any-Modality

Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs

UniAR: A Unified model for predicting human Attention and Responses on visual content

The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models

Fairness without Harm: An Influence-Guided Active Sampling Approach

Satformer: Accurate and Robust Traffic Data Estimation for Satellite Networks

In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization

Déjà Vu Memorization in Vision–Language Models

QVAE-Mole: The Quantum VAE with Spherical Latent Variable Learning for 3-D Molecule Generation

Generative Hierarchical Materials Search

Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning

EfficientCAPER: An End-to-End Framework for Fast and Robust Category-Level Articulated Object Pose Estimation

Navigating Chemical Space with Latent Flows

Unified Covariate Adjustment for Causal Inference

Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models

Bayesian Identification of the Hamiltonian Inductive Bias in Dynamical Systems

Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation

Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model

Rethinking Optimal Transport in Offline Reinforcement Learning

GraphVis: Boosting LLMs with Visual Knowledge Graph Integration

Exploration by Learning Diverse Skills through Successor State Representations

Sequoia: Scalable and Robust Speculative Decoding

Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness

Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting

Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts

PERIA: Perceive, Reason, Imagine, Act via Holistic Language and Vision Planning for Manipulation

SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning

Transductive Active Learning: Theory and Applications

Gorilla: Large Language Model Connected with Massive APIs

Make Your LLM Fully Utilize the Context

Solving Zero-Sum Markov Games with Continous State via Spectral Dynamic Embedding

Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild

Association Pattern-aware Fusion for Biological Entity Relationship Prediction

Should We Really Edit Language Models? On the Evaluation of Edited Language Models

Multi-Head Mixture-of-Experts

Dual-Perspective Activation: Efficient Channel Denoising via Joint Forward-Backward Criterion for Artificial Neural Networks

Self-Taught Recognizer: Toward Unsupervised Adaptation for Speech Foundation Models

HuRef: HUman-REadable Fingerprint for Large Language Models

The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms

(ends 2:00 PM)

noon

Expo Talk Panel:

Overcoming bottlenecks in AI development with flexible GPU cloud solutions

(ends 1:00 PM)

1 p.m.

Expo Workshop:

Hands-On AI for Everyone: Using Drones, Jumping Jacks, Gestures, and Skincare Product Labels

(ends 2:30 PM)

Expo Talk Panel:

Deep tabular data

(ends 2:00 PM)

Expo Talk Panel:

Industrial Applications of Distributional Preference Alignment of LLMs via Optimal Transport

(ends 2:00 PM)

Expo Workshop:

Open-Sora: Democratizing Efficient Video Production for All

(ends 2:30 PM)

Expo Workshop:

Streamlining Computer Vision Data Annotation with Segment Anything 2.1

(ends 2:30 PM)

Expo Workshop:

Post-training LLMs: From Algorithms to Training Infrastructures

(ends 2:30 PM)

Break:

Lunch (catered)

(ends 2:30 PM)

2:30 p.m.

Invited Talk:

From Seeing to Doing: Ascending the Ladder of Visual Intelligence

Fei-Fei Li

(ends 3:30 PM)

3:30 p.m.

Oral Session 2A: Agents [3:30-4:30]

Enhancing Preference-based Linear Bandits via Human Response Time

Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making

AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

(ends 4:30 PM)

Oral Session 2B: Reinforcement Learning [3:30-4:30]

Improving Environment Novelty Quantification for Effective Unsupervised Environment Design

The Sample-Communication Complexity Trade-off in Federated Q-Learning

Policy Learning from Tutorial Books via Understanding, Rehearsing and Introspecting

(ends 4:30 PM)

Oral Session 2C: Reinforcement Learning [3:30-4:30]

RL-GPT: Integrating Reinforcement Learning and Code-as-policy

Statistical Efficiency of Distributional Temporal Difference Learning

SeeA*: Efficient Exploration-Enhanced A* Search by Selective Sampling

(ends 4:30 PM)

Oral Session 2D: Generative Models [3:30-4:30]

Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs

VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

(ends 4:30 PM)

Overflow for Oral Session 2C: Reinforcement Learning [3:30-4:30]

(ends 4:30 PM)

Overflow for Oral Session 2B: Reinforcement Learning [3:30-4:30]

(ends 4:30 PM)

4:30 p.m.

Creative AI Session 4 [4:30-7:30]

Chairs: Jean Oh · Marcelo Coelho

s 4:30-7:30

[4:30] AI Nüshu

[4:30] AI TrackMate: Finally, Someone Who Will Give Your Music More Than Just “Sounds Great!”

[4:30] Ambiguity in AI: The Paradox of Gender Neutrality

[4:30] break me, genAI

[4:30] Creative Loss: Ambiguity, Uncertainty and Indeterminacy

[4:30] Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance

[4:30] Learning to Move, Learning to Play, Learning to Animate

[4:30] Ørigin

[4:30] Perfect Syntax

[4:30] Redefining Artistic Boundaries: A Real-Time Interactive Painting Robot for Musicians

[4:30] Rhythm Bots: A Sensitive Improvisational Environment

[4:30] SketcherX: AI-Driven Interactive Robotic drawing with Diffusion model and Vectorization Techniques

[4:30] Sketchy Collections: Exploring Digital Museum Collections by Drawing via CLIP

[4:30] Tesseract.art, a real-time generative AI interactive painting robot for multidisciplinary art

[4:30] Towards a ‘Non-Universal‘ Architecture: Designing with Others through Gestures (1:1 Scale)

[4:30] Towards Kinetic Manipulation of the Latent Space

(ends 7:30 PM)

Expo Talk Panel:

Empirical Rigor at Scale – or, How Not to Fool Yourself

(ends 5:30 PM)

Expo Talk Panel:

Can AI Save Us From Ourselves? Generative AI and Content Moderation

(ends 5:30 PM)

Expo Talk Panel:

Mastering Distributed Training: Best Practices for Scalable Model Training

(ends 5:30 PM)

Expo Talk Panel:

MegaBeam-Mistral-7B: Advancing Long-Context Processing for Real-World AI Applications

(ends 5:30 PM)

Break:

Coffee Break

(ends 5:30 PM)

Expo Talk Panel:

Learnings From Teams Training Large-Scale Models: Challenges and Solutions for Monitoring at Hyperscale

(ends 5:30 PM)

Expo Talk:

EUREKA: Evaluating and Understanding Large Foundation Models

(ends 5:30 PM)

Expo Talk:

Logarithmic Math in accurate and efficient AI inference accelerators

(ends 5:30 PM)

Poster Session 2 West [4:30-7:30]

Posters 4:30-7:30

Causal Bandits for Linear Structural Equation Models

Causal-learn: Causal Discovery in Python

Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data

Higher-Order Causal Message Passing for Experimentation with Complex Interference

Intervention and Conditioning in Causal Bayesian Networks

DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation

Causal Temporal Representation Learning with Nonstationary Sparse Transition

Proximal Causal Inference With Text Data

Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes

Identifiability Guarantees for Causal Disentanglement from Purely Observational Data

VastTrack: Vast Category Visual Object Tracking

RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content

AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

FindingEmo: An Image Dataset for Emotion Recognition in the Wild

Causal Discovery from Event Sequences by Local Cause-Effect Attribution

Causal discovery with endogenous context variables

Do causal predictors generalize better to new domains?

Sample Efficient Bayesian Learning of Causal Graphs from Interventions

Ordering-Based Causal Discovery for Linear and Nonlinear Relations

Natural Counterfactuals With Necessary Backtracking

Marrying Causal Representation Learning with Dynamical Systems for Science

Through the Looking-Glass: Tracing Shifts in AI Data Consent across the Web

ActionAtlas: A VideoQA Benchmark for Fine-grained Action Recognition

StreamBench: Towards Benchmarking Continuous Improvement of Language Agents

Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias

PUZZLES: A Benchmark for Neural Algorithmic Reasoning

Dispelling the Mirage of Progress in Offline MARL through Standardised Baselines and Evaluation

The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TBs of Astronomical Scientific Data

IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos

NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

SR-CACO-2: A Dataset for Confocal Fluorescence Microscopy Image Super-Resolution

BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text

RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation

RoleAgent: Building, Interacting, and Benchmarking High-quality Role-Playing Agents from Scripts

SLICE-100K: A Multimodal Dataset for Extrusion-based 3D Printing

SubjECTive-QA: A dataset for the subjective evaluation of answers in Earnings Call Transcripts (ECTs)

DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release

Evaluating Numerical Reasoning in Text-to-Image Models

NovoBench: Benchmarking Deep Learning-based \emph{De Novo} Sequencing Methods in Proteomics

ConvBench: A Multi-Turn Conversation Evaluation Benchmark with Hierarchical Ablation Capability for Large Vision-Language Models

WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks

Noisy Ostracods: A Fine-Grained, Imbalanced Real-World Dataset for Benchmarking Robust Machine Learning and Label Correction Methods

Benchmarking LLMs via Uncertainty Quantification

SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation

Norms for Managing Datasets: A Systematic Review of NeurIPS Datasets

BenchX: A Unified Benchmark Framework for Medical Vision-Language Pretraining on Chest X-Rays

Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making

MLLMGuard: A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models

Nuclear Fusion Diamond Polishing Dataset

MMLONGBENCH-DOC: Benchmarking Long-context Document Understanding with Visualizations

BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages

AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation

SS3DM: Benchmarking Street-View Surface Reconstruction with a Synthetic 3D Mesh Dataset

FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection

Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking

SureMap: Simultaneous mean estimation for single-task and multi-task disaggregated evaluation

Fairness-Aware Estimation of Graphical Models

Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images

Proportional Fairness in Non-Centroid Clustering

Towards Harmless Rawlsian Fairness Regardless of Demographic Prior

Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty

Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study

FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models

Reproducibility study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"

Reproducibility Study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"

Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs?

Fairness-Aware Meta-Learning via Nash Bargaining

DLAD: Improving Logits-based Detector without Logits from Black-box LLMs

On the Computational Landscape of Replicable Learning

Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance?

Provable Benefit of Cutout and CutMix for Feature Learning

Oracle-Efficient Differentially Private Learning with Public Data

Distribution Learning with Valid Outputs Beyond the Worst-Case

Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer

On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries

Near-Optimality of Contrastive Divergence Algorithms

4-bit Shampoo for Memory-Efficient Network Training

Derandomizing Multi-Distribution Learning

Online Estimation via Offline Estimation: An Information-Theoretic Framework

Solving Sparse \& High-Dimensional-Output Regression via Compression

Metric Transforms and Low Rank Representations of Kernels for Fast Attention

The Price of Implicit Bias in Adversarially Robust Generalization

Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data

Credit Attribution and Stable Compression

Entropy testing and its application to testing Bayesian networks

4+3 Phases of Compute-Optimal Neural Scaling Laws

Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics

Robust Mixture Learning when Outliers Overwhelm Small Groups

Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization

An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints

Robust Neural Contextual Bandit against Adversarial Corruptions

Saliency-driven Experience Replay for Continual Learning

Online Non-convex Learning in Dynamic Environments

Sample Complexity of Posted Pricing for a Single Item

Communication Bounds for the Distributed Experts Problem

Online Control with Adversarial Disturbance for Continuous-time Linear Systems

Online Composite Optimization Between Stochastic and Adversarial Environments

Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits

Almost Minimax Optimal Best Arm Identification in Piecewise Stationary Linear Bandits

FUGAL: Feature-fortified Unrestricted Graph Alignment

Multidimensional Fractional Programming for Normalized Cuts

Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations

Semidefinite Relaxations of the Gromov-Wasserstein Distance

Nesterov acceleration despite very noisy gradients

SkipPredict: When to Invest in Predictions for Scheduling

From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization

Why Warmup the Learning Rate? Underlying Mechanisms and Improvements

An Improved Empirical Fisher Approximation for Natural Gradient Descent

The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information

A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation

Piecewise-Stationary Bandits with Knapsacks

Revisiting Ensembling in One-Shot Federated Learning

CoBo: Collaborative Learning via Bilevel Optimization

BitDelta: Your Fine-Tune May Only Be Worth One Bit

FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction

Fundamental Convergence Analysis of Sharpness-Aware Minimization

Collaboration! Towards Robust Neural Methods for Routing Problems

Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming

Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way

Loss Landscape Characterization of Neural Networks without Over-Parametrization

A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization

Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data