NeurIPS 2024

4,493 papers

Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models

Sanae Lotfi, Yilun Kuang, Brandon Amos, Micah Goldblum, Marc Finzi

StreamFlow: Streamlined Multi-Frame Optical Flow Estimation for Video Sequences

SHANGKUN SUN, Jiaming Liu, Huaxia Li, Guoqing Liu, Thomas H Li

Sample Efficient Bayesian Learning of Causal Graphs from Interventions

Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu

Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels

Heeseong Shin, Chaehyun Kim, Sunghwan Hong, Seokju Cho, Anurag Arnab

AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models

Haiquan Lu, Yefan Zhou, Shiwei Liu, Zhangyang Wang, Michael W. Mahoney

Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space

Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann

A generalized neural tangent kernel for surrogate gradient learning

Luke Eilers, Raoul-Martin Memmesheimer, Sven Goedeke

Improving Deep Learning Optimization through Constrained Parameter Regularization

Jörg K.H. Franke, Michael Hefenbrock, Gregor Koehler, Frank Hutter

Data Mixture Inference Attack: BPE Tokenizers Reveal Training Data Compositions

Jonathan Hayase, Alisa Liu, Yejin Choi, Sewoong Oh, Noah A. Smith

Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination

Ruochen Liu, Hao Chen, Yuanchen Bei, Qijie Shen, Fangwei Zhong

Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities

Alexander Nikitin, Jannik Kossen, Yarin Gal, Pekka Marttinen

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

Aniket Das, Dheeraj Nagaraj, Soumyabrata Pal, Arun Sai Suggala, Prateek Varshney

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

Jung-hun Kim, Milan Vojnovic, Se-Young Yun

How Does Message Passing Improve Collaborative Filtering?

Clark Mingxuan Ju, William Shiao, Zhichun Guo, Yanfang Ye, Yozen Liu

SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training

Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng

MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs

Ziyu Liu, Tao Chu, Yuhang Zang, Xilin Wei, Xiaoyi Dong

Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss

Qiang Li, Hoi-To Wai

Invisible Image Watermarks Are Provably Removable Using Generative AI

Xuandong Zhao, Kexun Zhang, Zihao Su, Saastha Vasan, Ilya Grishchenko

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

Hao Shao, Shengju Qian, Han Xiao, Guanglu Song, Zhuofan Zong

Rethinking Model-based, Policy-based, and Value-based Reinforcement Learning via the Lens of Representation Complexity

Guhao Feng, Han Zhong

Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints

Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Federico Fusco

Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting

Runze Yang, Longbing Cao, Jianxun Li, jie Yang

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

Taira Tsuchiya, Shinji Ito

An effective framework for estimating individualized treatment rules

Joowon Lee, Jared D. Huling, Guanhua Chen

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

Jiapu Wang, Kai Sun, Linhao Luo, Wei Wei, Yongli Hu

Image-aware Evaluation of Generated Medical Reports

Gefen Dawidowicz, Elad Hirsch, Ayellet Tal

Generalized Linear Bandits with Limited Adaptivity

Ayush Sawarni, Nirjhar Das, Siddharth Barman, Gaurav Sinha

xMIL: Insightful Explanations for Multiple Instance Learning in Histopathology

Julius Hense, Mina Jamshidi Idaji, Oliver Eberle, Thomas Schnake, Jonas Dippel

Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis

Michael Crawshaw, Mingrui Liu

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

Arjun Subramonian, Jian Kang, Yizhou Sun

Localized Adaptive Risk Control

Matteo Zecchin, Osvaldo Simeone

Reparameterization invariance in approximate Bayesian inference

Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner

WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs

Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin

Graph Diffusion Transformers for Multi-Conditional Molecular Generation

Gang Liu, Jiaxin Xu, Tengfei Luo, Meng Jiang

Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection

Hui Wei, Zhixiang Wang, Kewei Zhang, Jiaqi Hou, YUANWEI LIU

Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques

Manh Cuong Dao, Phi Le Nguyen, Thao Nguyen Truong, Trong Nghia Hoang

DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection

Hongyu Shen, Yici Yan, Zhizhen Zhao

Kraken: Inherently Parallel Transformers For Efficient Multi-Device Inference

Rohan Baskar Prabhakar, Hengrui Zhang, David Wentzlaff

Reproducibility of predictive networks for mouse visual cortex

Polina Turishcheva, Max F. Burg, Fabian H. Sinz, Alexander S Ecker, Alexander S. Ecker

The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better

Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li

Visual Prompt Tuning in Null Space for Continual Learning

Yue Lu, Shizhou Zhang, De Cheng, Yinghui Xing, Nannan Wang

CiteME: Can Language Models Accurately Cite Scientific Claims?

Ori Press, Andreas Hochlehnert, Ameya Prabhu, Vishaal Udandarao, Ofir Press

DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving

Yuxuan Tong, Xiwen Zhang, Rui Wang, Ruidong Wu, Junxian He

In-Context Learning State Vector with Inner and Momentum Optimization

Dongfang Li, Zhenyu Liu, Xinshuo Hu, Zetian Sun, Baotian Hu

Understanding the Gains from Repeated Self-Distillation

Divyansh Pareek, Sewoong Oh, Simon S Du, Simon S. Du

MaskLLM: Learnable Semi-Structured Sparsity for Large Language Models

Gongfan Fang, Hongxu Yin, Saurav Muralidharan, Greg Heinrich, Jeff Pool

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

Yubo Ye, Maryam Toloubidokhti, Sumeet Vadhavkar, Xiajun Jiang, Huafeng Liu

Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness

Xiaoge Deng, Tao Sun, Shengwei Li, Dongsheng Li, Xicheng Lu

Limits of Transformer Language Models on Learning to Compose Algorithms

Jonathan Thomm, Giacomo Camposampiero, Aleksandar Terzic, Michael Hersche, Bernhard Schölkopf

Make Continual Learning Stronger via C-Flat

Ang Bian, Wei Li, Hangjie Yuan, Chengrong Yu, Mang Wang

MVGamba: Unify 3D Content Generation as State Space Sequence Modeling

Xuanyu Yi, Zike Wu, Qiuhong Shen, Qingshan Xu, Pan Zhou

Text2CAD: Generating Sequential CAD Designs from Beginner-to-Expert Level Text Prompts

Mohammad Sadil Khan, Sankalp Sinha, Talha Uddin Sheikh, Didier Stricker, Sk Aziz Ali

Optimal Multiclass U-Calibration Error and Beyond

Haipeng Luo, Spandan Senapati, Vatsal Sharan

Breaking Long-Tailed Learning Bottlenecks: A Controllable Paradigm with Hypernetwork-Generated Diverse Experts

Zhe Zhao, Haibin Wen, Zikang Wang, Pengkun Wang, Fanfu Wang

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights

Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li

Sharing Key Semantics in Transformer Makes Efficient Image Restoration

Bin Ren, Yawei Li, Jingyun Liang, Rakesh Ranjan, Mengyuan Liu

Understanding Information Storage and Transfer in Multi-Modal Large Language Models

Samyadeep Basu, Martin Grayson, Cecily Morrison, Besmira Nushi, Soheil Feizi

Locally Private and Robust Multi-Armed Bandits

Xingyu Zhou, Wei Zhang

You Only Cache Once: Decoder-Decoder Architectures for Language Models

Yutao Sun, Li Dong, Yi Zhu, Shaohan Huang, Wenhui Wang

Neural Isometries: Taming Transformations for Equivariant ML

Thomas W. Mitchel, Michael Taylor, Vincent Sitzmann

UrbanDataLayer: A Unified Data Pipeline for Urban Science

Yiheng Wang, Tianyu Wang, Yuying Zhang, Hongji Zhang, Haoyu Zheng

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

Tianle Gu, Zeyang Zhou, Kexin Huang, Dandan Liang, Yixu Wang

HonestLLM: Toward an Honest and Helpful Large Language Model

Chujie Gao, Siyuan Wu, Yue Huang, Dongping Chen, Qihui Zhang

TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy

Weichao Zhao, Hao Feng, Qi Liu, Jingqun Tang, Shu Wei

Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation

Lingxiao Zhao, Xueying Ding, Leman Akoglu

Learning to be Smooth: An End-to-End Differentiable Particle Smoother

Ali Younis, Erik B. Sudderth

A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning

Yuanning Cui, Zequn Sun, Wei Hu

Cross-Scale Self-Supervised Blind Image Deblurring via Implicit Neural Representation

Tianjing Zhang, Yuhui Quan, Hui Ji

On the Saturation Effects of Spectral Algorithms in Large Dimensions

Weihao Lu, Haobo Zhang, Yicheng Li, Qian Lin

Adapting Diffusion Models for Improved Prompt Compliance and Controllable Image Synthesis

Deepak Sridhar, Abhishek Peri, Rohith Rachala, Nuno Vasconcelos

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

Kai Sandbrink, Jan P. Bauer, Alexandra M. Proca, Christopher Summerfield, Ali Hummos

SplitNeRF: Split Sum Approximation Neural Field for Joint Geometry, Illumination, and Material Estimation

Jesus Zarzar, Bernard Ghanem

How Control Information Influences Multilingual Text Image Generation and Editing?

Boqiang Zhang, Zuan Gao, Yadong Qu, Hongtao Xie

Rethinking Imbalance in Image Super-Resolution for Efficient Inference

Wei Yu, Bowen Yang, Qinglin Liu, Jianing Li, Shengping Zhang

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

Zechen Bai, Tong He, Haiyang Mei, Pichao WANG, Ziteng Gao

Learning diffusion at lightspeed

Antonio Terpin, Nicolas Lanzetti, Martín Gadea, Florian Dorfler

TARP-VP: Towards Evaluation of Transferred Adversarial Robustness and Privacy on Label Mapping Visual Prompting Models

Zhen Chen, Yi Zhang, Fu Wang, Xingyu Zhao, Xiaowei Huang

LLM-based Skill Diffusion for Zero-shot Policy Adaptation

Woo Kyung Kim, Youngseok Lee, Jooyoung Kim, Honguk Woo

On f-Divergence Principled Domain Adaptation: An Improved Framework

Ziqiao Wang, Yongyi Mao

On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games

Awni Altabaa, Zhuoran Yang

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

Yang Zhou, Tan Li Hui Faith, Yanyu Xu, Sicong Leng, Xinxing Xu

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

Haoyu Dong, Huiqiao Fu, Wentao Xu, Zhehao Zhou, Chunlin Chen

DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors

Joseph Ortiz, Antoine Dedieu, Wolfgang Lehrach, J. Swaroop Guntupalli, Carter Wendelken

Exploring Adversarial Robustness of Deep State Space Models

Biqing Qi, Yiang Luo, Junqi Gao, Pengfei Li, Kai Tian

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

Elizabeth Collins-Woodfin, Inbar Seroussi, Begoña García Malaxechebarría, Andrew W. Mackenzie, Elliot Paquette

Unified Covariate Adjustment for Causal Inference

Yonghan Jung, Jin Tian, Elias Bareinboim

Sketching for Distributed Deep Learning: A Sharper Analysis

Mayank Shrivastava, Berivan Isik, Qiaobo Li, Sanmi Koyejo, Arindam Banerjee

Interpretable Lightweight Transformer via Unrolling of Learned Graph Smoothness Priors

Tam Thuc Do, Parham Eftekhar, Seyed Alireza Hosseini, Gene Cheung, Philip A. Chou

Weight Diffusion for Future: Learn to Generalize in Non-Stationary Environments

Mixue Xie, Shuang Li, Binhui Xie, Chi Harold Liu, Jian Liang

Cell ontology guided transcriptome foundation model

Xinyu Yuan, Zhihao Zhan, Zuobai Zhang, Manqi Zhou, Jianan Zhao

Supervised Kernel Thinning

Albert Gong, Kyuseong Choi, Raaz Dwivedi

IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation

Fei Shen, Jinhui Tang

Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning

Wuyang Chen, Jialin Song, Pu Ren, Shashank Subramanian, Dmitriy Morozov

Linking In-context Learning in Transformers to Human Episodic Memory

Li Ji-An, Corey Y Zhou, Marcus K. Benna, Marcelo G. Mattar

Federated Ensemble-Directed Offline Reinforcement Learning

Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai

Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning

Chong Ma, Hanqi Jiang, Wenting Chen, Yiwei Li, Zihao Wu

UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems

Zhi Zheng, Changliang Zhou, Xialiang Tong, Mingxuan Yuan, Zhenkun Wang

KnowGPT: Knowledge Graph based Prompting for Large Language Models

Qinggang Zhang, Junnan Dong, Hao Chen, Daochen Zha, Zailiang Yu

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

Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier De Chezelles

Exploiting Representation Curvature for Boundary Detection in Time Series

Yooju Shin, Jaehyun Park, Hwanjun Song, Susik Yoon, Byung Suk Lee