NeurIPS 2024

4,493 papers

BricksRL: A Platform for Democratizing Robotics and Reinforcement Learning Research and Education with LEGO

Sebastian Dittert, Vincent Moens, Gianni De Fabritiis

Prune and Repaint: Content-Aware Image Retargeting for any Ratio

Feihong Shen, CHAO LI, Yifeng Geng, Yongjian Deng, Hao Chen

Fast Rates for Bandit PAC Multiclass Classification

Liad Erez, Alon Cohen, Tomer Koren, Yishay Mansour, Shay Moran

Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text

Xinyang Li, Zhangyu Lai, Linning Xu, Yansong Qu, Liujuan Cao

IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors

Shenghe Zheng, Hongzhi Wang, Xianglong Liu

Spiking Neural Network as Adaptive Event Stream Slicer

Jiahang Cao, Mingyuan Sun, Ziqing Wang, Hao Cheng, Qiang Zhang

GIC: Gaussian-Informed Continuum for Physical Property Identification and Simulation

Junhao Cai, Yuji Yang, Weihao Yuan, Yisheng He, Zilong Dong

Transformers Represent Belief State Geometry in their Residual Stream

Adam S. Shai, Sarah E. Marzen, Lucas Teixeira, Alexander Gietelink Oldenziel, Paul M. Riechers

DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models

Bowen Wang, Jiuyang Chang, Yiming Qian, Guoxin Chen, Junhao Chen

NeoRL: Efficient Exploration for Nonepisodic RL

Bhavya Sukhija, Lenart Treven, Florian Dorfler, Stelian Coros, Andreas Krause

Towards Global Optimal Visual In-Context Learning Prompt Selection

Chengming Xu, Chen Liu, Yikai Wang, Yuan Yao, Yanwei Fu

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

Ziyi Wang, Yanbo Wang, Xumin Yu, Jie Zhou, Jiwen Lu

TableRAG: Million-Token Table Understanding with Language Models

Si-An Chen, Lesly Miculicich, Julian Martin Eisenschlos, Zifeng Wang, Zilong Wang

The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions

Zheng Wang, Geyong Min, Wenjie Ruan

ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration

Chi-Wei Hsiao, Yu-Lun Liu, Cheng-Kun Yang, Sheng-Po Kuo, Yucheun Kevin Jou

Full-Atom Peptide Design with Geometric Latent Diffusion

Xiangzhe Kong, Yinjun Jia, Wenbing Huang, Yang Liu

Universal Rates for Active Learning

Steve Hanneke, Amin Karbasi, Shay Moran, Grigoris Velegkas

Gaussian Process Bandits for Top-k Recommendations

Mohit Yadav, Daniel Sheldon, Cameron Musco

S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search

Gengmo Zhou, Zhen Wang, Feng Yu, Guolin Ke, Zhewei Wei

Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines

Edward Milsom, Ben Anson, Laurence Aitchison

Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning

Hao-Lun Hsu, Weixin Wang, Miroslav Pajic, Pan Xu

Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty

Elita Lobo, Justin Payan, Cyrus Cousins, Yair Zick

Oja's Algorithm for Streaming Sparse PCA

Syamantak Kumar, Purnamrita Sarkar

Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates

Jincheng Mei, Bo Dai, Alekh Agarwal, Sharan Vaswani, Anant Raj

Decoupled Kullback-Leibler Divergence Loss

Jiequan Cui, Zhuotao Tian, Zhisheng Zhong, Xiaojuan Qi, Bei Yu

FastDrag: Manipulate Anything in One Step

Xuanjia Zhao, Jian Guan, Congyi Fan, Dongli Xu, Youtian Lin

SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention

Róbert Csordás, Piotr Piękos, Kazuki Irie, Jürgen Schmidhuber

HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors

Panwang Pan, Zhuo Su, Chenguo Lin, Zhen Fan, Yongjie Zhang

Mitigating Spurious Correlations via Disagreement Probability

Hyeonggeun Han, Sehwan Kim, Hyungjun Joo, Sangwoo Hong, Jungwoo Lee

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

Chang Ma, Junlei Zhang, Zhihao Zhu, Cheng Yang, Yujiu Yang

Relationship Prompt Learning is Enough for Open-Vocabulary Semantic Segmentation

Jiahao Li, Yang Lu, Yuan Xie, Yanyun Qu

Unity by Diversity: Improved Representation Learning for Multimodal VAEs

Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin

UMB: Understanding Model Behavior for Open-World Object Detection

Xing Xi, Yangyang Huang, Zhijie Zhong, Ronghua Luo

TALoS: Enhancing Semantic Scene Completion via Test-time Adaptation on the Line of Sight

Hyun-Kurl Jang, Jihun Kim, Hyeokjun Kweon, Kuk-Jin Yoon

Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control

Gunshi Gupta, Karmesh Yadav, Yarin Gal, Zsolt Kira, Dhruv Batra

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series

Vijay Ekambaram, Arindam Jati, Pankaj Dayama, Sumanta Mukherjee, Nam H. Nguyen

Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy

Shengfang Zhai, Huanran Chen, Yinpeng Dong, Jiajun Li, Qingni Shen

Efficient Lifelong Model Evaluation in an Era of Rapid Progress

Ameya Prabhu, Vishaal Udandarao, Philip H.S. Torr, Matthias Bethge, Adel Bibi

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

Tiansheng Huang, Sihao Hu, Ling Liu

Contrastive dimension reduction: when and how?

Sam Hawke, YueEn Ma, Didong Li

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

Taisuke Yasuda, Kyriakos Axiotis, Gang Fu, Mohammadhossein Bateni, Vahab Mirrokni

Efficient Large Multi-modal Models via Visual Context Compression

Jieneng Chen, Luoxin Ye, Ju He, Zhao-Yang Wang, Daniel Khashabi

Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling

Grigory Bartosh, Dmitry Vetrov, Christian A. Naesseth

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

Zhan Zhuang, Yulong Zhang, Xuehao Wang, Jiangang Lu, Ying Wei

Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees

Yu Gui, Ying Jin, Zhimei Ren

Hybrid Mamba for Few-Shot Segmentation

Qianxiong Xu, Xuanyi Liu, Lanyun Zhu, Guosheng Lin, Cheng Long

On the Expressive Power of Tree-Structured Probabilistic Circuits

Lang Yin, Han Zhao

Aligning to Thousands of Preferences via System Message Generalization

Seongyun Lee, Sue Hyun Park, Seungone Kim, Minjoon Seo

Distributed Least Squares in Small Space via Sketching and Bias Reduction

Sachin Garg, Kevin Tan, Michał Dereziński

Efficient Leverage Score Sampling for Tensor Train Decomposition

Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik, Guillaume Rabusseau

Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization

Amirhossein Saberi, Amir Najafi, Amin Behjati, Ala Emrani, Yasaman Zolfit

GeoNLF: Geometry guided Pose-Free Neural LiDAR Fields

Weiyi Xue, Zehan Zheng, Fan Lu, Haiyun Wei, Guang Chen

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

Anqi Mao, Mehryar Mohri, Yutao Zhong

Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift

Jiawei Ge, Debarghya Mukherjee, Jianqing Fan

Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus

Terufumi Morishita, Gaku Morio, Atsuki Yamaguchi, Yasuhiro Sogawa

Solving Inverse Problems via Diffusion Optimal Control

Henry Li, Marcus Pereira

Scalable Optimization in the Modular Norm

Tim Large, Yang Liu, Minyoung Huh, Hyojin Bahng, Phillip Isola

Scalable Early Childhood Reading Performance Prediction

Zhongkai Shangguan, Zanming Huang, Eshed Ohn-Bar, Ola Ozernov-Palchik, Derek Kosty

Secret Collusion among AI Agents: Multi-Agent Deception via Steganography

Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip H.S. Torr

Graph Edit Distance with General Costs Using Neural Set Divergence

Eeshaan Jain, Indradyumna Roy, Saswat Meher, Soumen Chakrabarti, Abir De

Self-Play Fine-tuning of Diffusion Models for Text-to-image Generation

Huizhuo Yuan, Zixiang Chen, Kaixuan Ji, Quanquan Gu

On Affine Homotopy between Language Encoders

Robin S. M. Chan, Reda Boumasmoud, Anej Svete, Yuxin Ren, Qipeng Guo

State Chrono Representation for Enhancing Generalization in Reinforcement Learning

Jianda Chen, Wen Zheng Terence Ng, Zichen Chen, Sinno Jialin Pan, Tianwei Zhang

OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents

Zihao Wang, Shaofei Cai, Zhancun Mu, Haowei Lin, Ceyao Zhang

Physical Consistency Bridges Heterogeneous Data in Molecular Multi-Task Learning

Yuxuan Ren, Dihan Zheng, Chang Liu, Peiran Jin, Yu Shi

Symmetries in Overparametrized Neural Networks: A Mean Field View

Javier Maass Martínez, Joaquin Fontbona

Are Graph Neural Networks Optimal Approximation Algorithms?

Morris Yau, Nikolaos Karalias, Eric Lu, Jessica Xu, Stefanie Jegelka

Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox

Haohui Wang, Weijie Guan, Jianpeng Chen, Zi Wang, Da-Wei Zhou

Towards Stable Representations for Protein Interface Prediction

Ziqi Gao, Zijing Liu, Yu Li, Jia Li

Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift

Jiayun Wu, Jiashuo Liu, Peng Cui, Zhiwei Steven Wu

Pure Message Passing Can Estimate Common Neighbor for Link Prediction

Kaiwen Dong, Zhichun Guo, Nitesh V. Chawla

Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms

Jiechao Guan, Hui Xiong

Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning

Beyazit Yalcinkaya, Niklas Lauffer, Marcell Vazquez-Chanlatte, Sanjit A. Seshia

Safe Exploitative Play with Untrusted Type Beliefs

Tongxin Li, Tinashe Handina, Shaolei Ren, Adam Wierman

Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously

Yihan Wang, Yifan Zhu, Xiao-Shan Gao

SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation

Yixia Li, Boya Xiong, Guanhua Chen, Yun Chen

Order-Independence Without Fine Tuning

Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork

Generative Retrieval Meets Multi-Graded Relevance

Yubao Tang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke, Wei Chen

Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD

Jie Hu, Yi-Ting Ma, Do-Young Eun, Do Young Eun

Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers

Lorenzo Tiberi, Francesca Mignacco, Kazuki Irie, Haim Sompolinsky

Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling

Sili Huang, Jifeng Hu, Zhejian Yang, Liwei Yang, Tao Luo

Accelerating ERM for data-driven algorithm design using output-sensitive techniques

Maria-Florina Balcan, Christopher Seiler, Dravyansh Sharma

Integrating GNN and Neural ODEs for Estimating Non-Reciprocal Two-Body Interactions in Mixed-Species Collective Motion

Masahito Uwamichi, Simon K. Schnyder, Tetsuya J. Kobayashi, Satoshi Sawai

Poseidon: Efficient Foundation Models for PDEs

Maximilian Herde, Bogdan Raonic, Tobias Rohner, Roger Käppeli, Roberto Molinaro

Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective

Xufeng Cai, Cheuk Yin Lin, Jelena Diakonikolas

ADOPT: Modified Adam Can Converge with Any β_2 with the Optimal Rate

Shohei Taniguchi, Keno Harada, Gouki Minegishi, Yuta Oshima, Seong Cheol Jeong

PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond

Chen Song, Zhenxiao Liang, Bo Sun, Qixing Huang

Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees

Taiki Miyagawa, Takeru Yokota

EEG2Video: Towards Decoding Dynamic Visual Perception from EEG Signals

Xuan-Hao Liu, Yan-Kai Liu, Yansen Wang, Kan Ren, Hanwen Shi

DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models

Shangqian Gao, Chi-Heng Lin, Ting Hua, Tang Zheng, Yilin Shen

Automatically Learning Hybrid Digital Twins of Dynamical Systems

Samuel Holt, Tennison Liu, Mihaela van der Schaar

Training an Open-Vocabulary Monocular 3D Detection Model without 3D Data

Rui Huang, Henry Zheng, Yan Wang, Zhuofan Xia, Marco Pavone

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

Andrei Margeloiu, Xiangjian Jiang, Nikola Simidjievski, Mateja Jamnik

Universal In-Context Approximation By Prompting Fully Recurrent Models

Aleksandar Petrov, Tom A. Lamb, Alasdair Paren, Philip H.S. Torr, Adel Bibi

Can Transformers Smell Like Humans?

Farzaneh Taleb, Miguel Vasco, Antônio H. Ribeiro, Mårten Björkman, Danica Kragic

Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity

Kaiqu Liang, Zixu Zhang, Jaime Fernández Fisac

Active preference learning for ordering items in- and out-of-sample

Herman Bergström, Emil Carlsson, Devdatt Dubhashi, Fredrik D Johansson, Fredrik D. Johansson

Enriching Disentanglement: From Logical Definitions to Quantitative Metrics

Yivan Zhang, Masashi Sugiyama

Boosted Conformal Prediction Intervals

Ran Xie, Rina Foygel Barber, Emmanuel J. Candès

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

Jannik Franzen, Claudia Winklmayr, Vanessa E. Guarino, Christoph Karg, Xiaoyan Yu