NeurIPS 2024

4,493 papers

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

Xiaolei Liu, Shaoshuai Li, Kaixin Gao, Binfeng Wang

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

Shaoteng Liu, Haoqi Yuan, Minda Hu, Yanwei Li, Yukang Chen

FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion

Zhenheng Tang, Yonggang Zhang, Peijie Dong, Yiu-ming Cheung, Amelie Chi Zhou

Probabilistic Graph Rewiring via Virtual Nodes

Chendi Qian, Andrei Manolache, Christopher Morris, Mathias Niepert

The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof

Derek Lim, Theo (Moe) Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka

Perplexity-aware Correction for Robust Alignment with Noisy Preferences

Keyi Kong, Xilie Xu, Di Wang, Jingfeng ZHANG, Mohan Kankanhalli

OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation

Junke Wang, Yi Jiang, Zehuan Yuan, Binyue Peng, Zuxuan Wu

DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection

Shihao Tu, Linfeng Cao, Daoze Zhang, Junru Chen, Lvbin Ma

GTBench: Uncovering the Strategic Reasoning Capabilities of LLMs via Game-Theoretic Evaluations

Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun

Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models

Hanxiao Zhang, Lin Ju, Chan Wu, Jinjing Huang, Youshao Xiao

Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training

Pihe Hu, Shaolong Li, Zhuoran Li, Ling Pan, Longbo Huang

Don't Look Twice: Faster Video Transformers with Run-Length Tokenization

Rohan Choudhury, Guanglei Zhu, Sihan Liu, Koichiro Niinuma, Kris M. Kitani

Test Where Decisions Matter: Importance-driven Testing for Deep Reinforcement Learning

Stefan Pranger, Hana Chockler, Martin Tappler, Bettina Könighofer

From Transparent to Opaque: Rethinking Neural Implicit Surfaces with α-NeuS

Haoran Zhang, Junkai Deng, Xuhui Chen, Fei Hou, Wencheng Wang

M$^3$GPT: An Advanced Multimodal, Multitask Framework for Motion Comprehension and Generation

Mingshuang Luo, Ruibing Hou, Zhuo Li, Hong Chang, Zimo Liu

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

Qihao Zhou, Haishan Ye, Luo Luo

Scalable DBSCAN with Random Projections

HaoChuan Xu, Ninh Pham

Generative Forests

Richard Nock, Mathieu Guillame-Bert

FineCLIP: Self-distilled Region-based CLIP for Better Fine-grained Understanding

Dong Jing, Xiaolong He, Yutian Luo, Nanyi Fei, Guoxing Yang

How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad

Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Colin Sandon, Omid Saremi

Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data

Thibault Simonetto, Salah Ghamizi, Maxime Cordy

Multi-Agent Imitation Learning: Value is Easy, Regret is Hard

Jingwu Tang, Gokul Swamy, Fei Fang, Zhiwei Steven Wu

Optimal deep learning of holomorphic operators between Banach spaces

Ben Adcock, Nick Dexter, Sebastian Moraga

AlphaMath Almost Zero: Process Supervision without Process

Guoxin Chen, Minpeng Liao, Chengxi Li, Kai Fan

Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment

Weichao Zhou, Wenchao Li

UDPM: Upsampling Diffusion Probabilistic Models

Shady Abu-Hussein, Raja Giryes

Learning Truncated Causal History Model for Video Restoration

Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh, Di Niu

Quantifying and Optimizing Global Faithfulness in Persona-driven Role-playing

Letian Peng, Jingbo Shang

GenRL: Multimodal-foundation world models for generalization in embodied agents

Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron Courville, Sai Rajeswar

First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs

Ben Norman, Jeff Clune

On Softmax Direct Preference Optimization for Recommendation

Yuxin Chen, Junfei Tan, An Zhang, Zhengyi Yang, Leheng Sheng

MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space

Jiangwei Weng, Zhiqiang Yan, Ying Tai, Jianjun Qian, Jian Yang

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

Haoran Luo, Haihong E, Yuhao Yang, Tianyu Yao, Yikai Guo

Efficiency for Free: Ideal Data Are Transportable Representations

peng sun, Yi Jiang, Tao LIN

Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing

Siyi Chen, Huijie Zhang, Minzhe Guo, Yifu Lu, Peng Wang

A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning

Tom Yan, Zachary Lipton

Diffeomorphic interpolation for efficient persistence-based topological optimization

Mathieu Carrière, Marc Theveneau, Theo Lacombe

4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs

Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li

Learning from Pattern Completion: Self-supervised Controllable Generation

Zhiqiang Chen, Guofan Fan, Jinying Gao, Lei Ma, Bo Lei

Inverse Factorized Soft Q-Learning for Cooperative Multi-agent Imitation Learning

The Viet Bui, Tien Mai, Thanh Hong Nguyen

Streaming Bayes GFlowNets

Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita

Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling

Harry Jake Cunningham, Giorgio Giannone, Mingtian Zhang, Marc Peter Deisenroth

On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift

Pratiksha Thaker, Amrith Setlur, Zhiwei Steven Wu, Virginia Smith

Are We on the Right Way for Evaluating Large Vision-Language Models?

Lin Chen, Jinsong Li, Xiaoyi Dong, Pan Zhang, Yuhang Zang

Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking

Yuwei Zhang, Tong Xia, Jing Han, Yu Yvonne Wu, Georgios Rizos

A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation

Tomoya Sakai, Haoxiang Qiu, Takayuki Katsuki, Daiki Kimura, Takayuki Osogami

Contextual Linear Optimization with Bandit Feedback

Yichun Hu, Nathan Kallus, Xiaojie Mao, Yanchen Wu

Evaluating the World Model Implicit in a Generative Model

Keyon Vafa, Justin Y. Chen, Ashesh Rambachan, Jon Kleinberg, Sendhil Mullainathan

Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators

Changze Lv, Dongqi Han, Yansen Wang, Xiaoqing Zheng, Xuanjing Huang

Fast samplers for Inverse Problems in Iterative Refinement models

Kushagra Pandey, Ruihan Yang, Stephan Mandt

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

Ying Yang, De Cheng, Chaowei Fang, Yubiao Wang, Changzhe Jiao

When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search

Xuan Chen, Yuzhou Nie, Wenbo Guo, Xiangyu Zhang

Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction

Anton Rodomanov, Xiaowen Jiang, Sebastian Stich

Achieving Tractable Minimax Optimal Regret in Average Reward MDPs

Victor Boone, Zihan Zhang

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

Qidong Liu, Xian Wu, Yejing Wang, Zijian Zhang, Feng Tian

DAPE: Data-Adaptive Positional Encoding for Length Extrapolation

Chuanyang Zheng, Yihang Gao, Han Shi, Minbin Huang, Jingyao Li

Better by default: Strong pre-tuned MLPs and boosted trees on tabular data

David Holzmüller, Leo Grinsztajn, Ingo Steinwart

Constrained Diffusion Models via Dual Training

Shervin Khalafi, Dongsheng Ding, Alejandro Ribeiro

Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data

Xuxing Chen, Abhishek Roy, Yifan Hu, Krishnakumar Balasubramanian

Generalization of Hamiltonian algorithms

Andreas Maurer

Policy Mirror Descent with Lookahead

Kimon Protopapas, Anas Barakat

ReactZyme: A Benchmark for Enzyme-Reaction Prediction

Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf

Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement

Zhehao Huang, Xinwen Cheng, JingHao Zheng, Haoran Wang, Zhengbao He

Geometric Exploitation for Indoor Panoramic Semantic Segmentation

Duc Cao Dinh, Seok Joon Kim, Kyusung Cho

Multi-Instance Partial-Label Learning with Margin Adjustment

Wei Tang, Yin-Fang Yang, Zhaofei Wang, Weijia Zhang, Min-ling Zhang

Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers

Qiufeng Wang, Xu Yang, Fu Feng, Jing Wang, Xin Geng

Improving Decision Sparsity

Yiyang Sun, Tong Wang, Cynthia Rudin

Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?

Jiacheng Cen, Anyi Li, Ning Lin, Yuxiang Ren, Zihe Wang

LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages

Andrew Bean, Simi Hellsten, Harry Mayne, Jabez Magomere, Ethan A. Chi

What Matters in Graph Class Incremental Learning? An Information Preservation Perspective

Jialu Li, Yu Wang, Pengfei Zhu, Wanyu Lin, Qinghua Hu

Automated Multi-level Preference for MLLMs

Mengxi Zhang, Wenhao Wu, Yu Lu, Yuxin Song, Kang Rong

Capturing the denoising effect of PCA via compression ratio

Chandra Sekhar Mukherjee, Nikhil Deorkar, Jiapeng Zhang

Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms

Felix Petersen, Christian Borgelt, Tobias Sutter, Hilde Kuehne, Oliver Deussen

Smoke and Mirrors in Causal Downstream Tasks

Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello

UltraMedical: Building Specialized Generalists in Biomedicine

Kaiyan Zhang, Sihang Zeng, Ermo Hua, Ning Ding, Zhang-Ren Chen

Score Distillation via Reparametrized DDIM

Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan Greenewald, Vitor Campagnolo Guizilini, Timur Bagautdinov

AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoning

Shirley Wu, Shiyu Zhao, Qian Huang, Kexin Huang, Michihiro Yasunaga

Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems

Vincent Cohen-Addad, Tommaso d'Orsi, Anupam Gupta, Euiwoong Lee, Debmalya Panigrahi

Nonlinear dynamics of localization in neural receptive fields

Leon Lufkin, Andrew Saxe, Erin Grant

Learning 1D Causal Visual Representation with De-focus Attention Networks

Chenxin Tao, Xizhou Zhu, Shiqian Su, Lewei Lu, Changyao Tian

Archaeoscape: Bringing Aerial Laser Scanning Archaeology to the Deep Learning Era

Yohann Perron, Vladyslav Sydorov, Adam P. Wijker, Damian Evans, Christophe Pottier

A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem

Pankaj K. Agarwal, Sharath Raghvendra, Pouyan Shirzadian, Keegan Yao

Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling

Mingze Wang, Weinan E

PhyRecon: Physically Plausible Neural Scene Reconstruction

Junfeng Ni, Yixin Chen, Bohan Jing, Nan Jiang, Bin Wang

AdanCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer

Yitao Xu, Tong Zhang, Sabine Süsstrunk

Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model

Yuheng Shi, Minjing Dong, Chang Xu

GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching

Haibin He, Maoyuan Ye, Jing Zhang, Juhua Liu, Bo Du

Geometric Trajectory Diffusion Models

Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon

Decentralized Noncooperative Games with Coupled Decision-Dependent Distributions

Wenjing YAN, Xuanyu Cao

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

Yuhan Zhu, Yuyang Ji, Zhiyu Zhao, Gangshan Wu, Limin Wang

Least Squares Regression Can Exhibit Under-Parameterized Double Descent

Xinyue Li, Rishi Sonthalia

Generative Fractional Diffusion Models

Gabriel Nobis, Maximilian Springenberg, Marco Aversa, Michael Detzel, Rembert Daems

MathPile: A Billion-Token-Scale Pretraining Corpus for Math

Zengzhi Wang, Xuefeng Li, Rui Xia, Pengfei Liu

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

Sattar Vakili, Julia Olkhovskaya

Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge

Heewoong Noh, Namkyeong Lee, Gyoung S. Na, Chanyoung Park

Mirror and Preconditioned Gradient Descent in Wasserstein Space

Clément Bonet, Théo Uscidda, Adam David, Pierre-Cyril Aubin-Frankowski, Anna Korba

DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning

Zijian Zhou, Xiaoqiang Lin, Xinyi Xu, Alok Prakash, Daniela Rus

Cloud Object Detector Adaptation by Integrating Different Source Knowledge

Shuaifeng Li, Mao Ye, Lihua Zhou, Nianxin Li, Siying Xiao

Cross-video Identity Correlating for Person Re-identification Pre-training

Jialong Zuo, Ying Nie, Hanyu Zhou, Huaxin Zhang, Haoyu Wang

ReMAP: Neural Model Reprogramming with Network Inversion and Retrieval-Augmented Mapping for Adaptive Motion Forecasting

Sharmita Dey, Sarath Ravindran Nair