NeurIPS 2024

4,493 papers

Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators

Benedikt Alkin, Andreas Fürst, Simon Schmid, Lukas Gruber, Markus Holzleitner

Pre-trained Large Language Models Use Fourier Features to Compute Addition

Tianyi Zhou, Deqing Fu, Vatsal Sharan, Robin Jia

A Simple Image Segmentation Framework via In-Context Examples

Yang Liu, Chenchen Jing, Hengtao Li, Muzhi Zhu, Hao Chen

LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models

Haitao Li, You Chen, Qingyao Ai, Yueyue Wu, Ruizhe Zhang

Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut

Hongyu Cheng, Sammy Khalife, Barbara Fiedorowicz, Amitabh Basu

First-Order Minimax Bilevel Optimization

Yifan Yang, Zhaofeng Si, Siwei Lyu, Kaiyi Ji

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

Rayen Dhahri, Alexander Immer, Betrand Charpentier, Stephan Günnemann, Vincent Fortuin

BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models

Qijun Luo, Hengxu Yu, Xiao Li

Aligning Diffusion Models by Optimizing Human Utility

Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Yusuke Kato, Kazuki Kozuka

Pedestrian-Centric 3D Pre-collision Pose and Shape Estimation from Dashcam Perspective

Meijun Wang, Yu Meng, Zhongwei Qiu, Chao Zheng, Yan Xu

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

Yufei Guo, Yuanpei Chen, Zecheng Hao, Weihang Peng, Zhou Jie

ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization

Haoran You, Yipin Guo, Yichao Fu, Wei Zhou, Huihong Shi

DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection

Jia Syuen Lim, Zhuoxiao Chen, Mahsa Baktashmotlagh, Zhi Chen, Xin Yu

Faster Repeated Evasion Attacks in Tree Ensembles

Lorenzo Cascioli, Laurens Devos, Ondrej Kuzelka, Jesse Davis

Statistical Efficiency of Distributional Temporal Difference Learning

Yang Peng, Liangyu Zhang, Zhihua Zhang

A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression

Tin Sum Cheng, Aurelien Lucchi, Anastasis Kratsios, David Belius

Global Rewards in Restless Multi-Armed Bandits

Naveen Raman, Zheyuan Ryan Shi, Fei Fang

Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models

Sangwoong Yoon, Himchan Hwang, Dohyun Kwon, Yung-kyun Noh, Frank C. Park

Controlled maximal variability along with reliable performance in recurrent neural networks

Chiara Mastrogiuseppe, Ruben Moreno-Bote

Grammar-Aligned Decoding

Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, Loris D'Antoni

CLIP in Mirror: Disentangling text from visual images through reflection

Tiancheng Wang, Yuguang Yang, Linlin Yang, Shaohui Lin, Juan Zhang

One-to-Multiple: A Progressive Style Transfer Unsupervised Domain-Adaptive Framework for Kidney Tumor Segmentation

Kai Hu, Jinhao Li, yuan zhang, Xiongjun Ye, Xieping Gao

Long-range Brain Graph Transformer

Shuo Yu, Shan Jin, Ming Li, Tabinda Sarwar, Feng Xia

Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training

Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli

SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization

Qian Chen, Tianjian Zhang, Linxin Yang, Qingyu Han, Akang Wang

Transcoders find interpretable LLM feature circuits

Jacob Dunefsky, Philippe Chlenski, Neel Nanda

PAC-Bayes-Chernoff bounds for unbounded losses

Ioar Casado, Luis A. Ortega, Aritz Pérez, Andrés R. Masegosa

Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics

Xiaodan Chen, Xiucheng Li, Xinyang Chen, Zhijun Li

Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification

Haolin Liu, Artin Tajdini, Andrew Wagenmaker, Chen-Yu Wei

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

Joao Monteiro, Pierre-André Noël, Étienne Marcotte, Sai Rajeswar, Valentina Zantedeschi

Causal Discovery from Event Sequences by Local Cause-Effect Attribution

Joscha Cüppers, Sascha Xu, Ahmed Musa, Jilles Vreeken

Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in LLMs

Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng

Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity

Hanlin Gu, Win Kent Ong, Chee Seng Chan, Lixin Fan

MiSO: Optimizing brain stimulation to create neural population activity states

Yuki Minai, Joana Soldado-Magraner, Matthew A. Smith, Byron M. Yu

Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion

Boyuan Chen, Diego Martí Monsó, Yilun Du, Max Simchowitz, Russ Tedrake

SIRIUS : Contexual Sparisty with Correction for Efficient LLMs

Yang Zhou, Zhuoming Chen, Zhaozhuo Xu, Xi Victoria Lin, Beidi Chen

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

Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi

The Implicit Bias of Adam on Separable Data

Chenyang Zhang, Difan Zou, Yuan Cao

Linear Causal Bandits: Unknown Graph and Soft Interventions

Zirui Yan, Ali Tajer

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

Chenyu Yang, Xizhou Zhu, Jinguo Zhu, Weijie Su, Junjie Wang

Data Free Backdoor Attacks

Bochuan Cao, Jinyuan Jia, Chuxuan Hu, Wenbo Guo, Zhen Xiang

Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions

Nivasini Ananthakrishnan, Nika Haghtalab, Chara Podimata, Kunhe Yang

Is Score Matching Suitable for Estimating Point Processes?

Haoqun Cao, Zizhuo Meng, Tianjun Ke, Feng Zhou

If You Want to Be Robust, Be Wary of Initialization

Sofiane Ennadir, Johannes F. Lutzeyer, Michalis Vazirgiannis, El Houcine Bergou

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

Shan Chen, Jack Gallifant, Mingye Gao, Pedro Moreira, Nikolaj Munch

A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems

Mohammad-Amin Charusaie, Samira Samadi

Ensemble sampling for linear bandits: small ensembles suffice

David Janz, Alexander E. Litvak, Csaba Szepesvári

Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models

Liulei Li, Wenguan Wang, Yi Yang

DRACO: A Denoising-Reconstruction Autoencoder for Cryo-EM

Yingjun Shen, Haizhao Dai, Qihe Chen, Yan Zeng, Jiakai Zhang

Identifying Equivalent Training Dynamics

William T. Redman, Juan Bello-Rivas, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis

A Simple yet Universal Framework for Depth Completion

Jin-Hwi Park, Hae-Gon Jeon

Dense Associative Memory Through the Lens of Random Features

Benjamin Hoover, Duen Horng Chau, Hendrik Strobelt, Parikshit Ram, Dmitry Krotov

Consistency Diffusion Bridge Models

Guande He, Kaiwen Zheng, Jianfei Chen, Fan Bao, Jun Zhu

Neuro-Symbolic Data Generation for Math Reasoning

Zenan Li, Zhi Zhou, Yuan Yao, Yu-feng Li, Chun Cao

DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs

Lingchen Meng, Jianwei Yang, Rui Tian, Xiyang Dai, Zuxuan Wu

Coherent 3D Scene Diffusion From a Single RGB Image

Manuel Dahnert, Angela Dai, Norman Müller, Matthias Nießner

Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms

Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee

NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mapping

Yamin Li, Ange Lou, Ziyuan Xu, Shengchao Zhang, Shiyu Wang

Cross-Modality Perturbation Synergy Attack for Person Re-identification

Yunpeng Gong, Zhun Zhong, Yansong Qu, Zhiming Luo, Rongrong Ji

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

Wanghan Xu, Fenghua Ling, Wenlong Zhang, Tao Han, Hao Chen

Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers

Jonas Ngnawé, Sabyasachi Sahoo, Yann Pequignot, Frederic Precioso, Christian Gagné

On conditional diffusion models for PDE simulations

Aliaksandra Shysheya, Cristiana Diaconu, Federico Bergamin, Paris Perdikaris, José Miguel Hernández-Lobato

Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization

Kai Hu, Weichen Yu, Yining Li, Tianjun Yao, Xiang Li

Why Do We Need Weight Decay in Modern Deep Learning?

Francesco D'Angelo, Maksym Andriushchenko, Aditya Varre, Nicolas Flammarion

Unified Generative and Discriminative Training for Multi-modal Large Language Models

Wei Chow, Juncheng Li, Qifan Yu, Kaihang Pan, Hao Fei

Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information

Marco Miani, Lorenzo Beretta, Søren Hauberg

On Differentially Private U Statistics

Kamalika Chaudhuri, Po-ling Loh, Shourya Pandey, Purnamrita Sarkar

Communication-Efficient Federated Group Distributionally Robust Optimization

Zhishuai Guo, Tianbao Yang

A two-scale Complexity Measure for Deep Learning Models

Massimiliano Datres, Gian Paolo Leonardi, Alessio Figalli, David Sutter

Parallel Backpropagation for Shared-Feature Visualization

Alexander Lappe, Anna Bognár, Ghazaleh Ghamkhari Nejad, Albert Mukovskiy, Lucas Martini

Boosting the Potential of Large Language Models with an Intelligent Information Assistant

Yujia Zhou, Zheng Liu, Zhicheng Dou

SnapKV: LLM Knows What You are Looking for Before Generation

Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli

ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs

Irene Huang, Wei LIN, M. Jehanzeb Mirza, Jacob A. Hansen, Sivan Doveh

FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation

Christopher T. H. Teo, Milad Abdollahzadeh, Xinda Ma, Ngai-Man Cheung

Distribution Learning with Valid Outputs Beyond the Worst-Case

Nick Rittler, Kamalika Chaudhuri

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

Qi Lv, Xiang Deng, Gongwei Chen, Michael Yu Wang, Liqiang Nie

Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning

Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff, Kevin Jamieson

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

Huanjin Wu, Xinyu Ye, Junchi Yan

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

Wenjia Xie, Hao Wang, Luankang Zhang, Rui Zhou, Defu Lian

Out-Of-Distribution Detection with Diversification (Provably)

Haiyun Yao, Zongbo Han, Huazhu Fu, Xi Peng, Qinghua Hu

Not so griddy: Internal representations of RNNs path integrating more than one agent

William T. Redman, Francisco Acosta, Santiago Acosta-Mendoza, Nina Miolane

Implicit Optimization Bias of Next-token Prediction in Linear Models

CHRISTOS THRAMPOULIDIS

Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models

Regev Cohen, Idan Kligvasser, Ehud Rivlin, Daniel Freedman

ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping

Mingzhen Huang, Jialing Cai, Shan Jia, Vishnu Suresh Lokhande, Siwei Lyu

Learning the Expected Core of Strictly Convex Stochastic Cooperative Games

Nam Phuong Tran, The Anh Ta, Shuqing Shi, Debmalya Mandal, Yali Du

FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations

Ziyao Wang, Zheyu Shen, Yexiao He, Guoheng Sun, Hongyi Wang

Efficient multi-prompt evaluation of LLMs

Felipe Maia Polo, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj

Is Your HD Map Constructor Reliable under Sensor Corruptions?

Xiaoshuai Hao, Mengchuan Wei, Yifan Yang, Haimei Zhao, Hui Zhang

Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models

Junjiao Tian, Chengyue Huang, Zsolt Kira

TFG: Unified Training-Free Guidance for Diffusion Models

Haotian Ye, Haowei Lin, Jiaqi Han, Minkai Xu, Sheng Liu

RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modeling

Tianhang Wang, Fan Lu, Zehan Zheng, Guang Chen, changjun jiang

Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation

Eyal Michaeli, Ohad Fried

Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure

Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta

Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective

Chengsen Wang, Qi Qi, Jingyu Wang, Haifeng Sun, Zirui Zhuang

Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics

Jonas Spinner, Victor Bresó, Pim de Haan, Tilman Plehn, Jesse Thaler

Quadratic Quantum Variational Monte Carlo

Baiyu Su, Qiang Liu

Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning

Brandon Huang, Chancharik Mitra, Assaf Arbelle, Leonid Karlinsky, Trevor Darrell

SeafloorAI: A Large-scale Vision-Language Dataset for Seafloor Geological Survey

Kien X. Nguyen, Fengchun Qiao, Arthur Trembanis, Xi Peng

Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning

Xinran Li, Ling Pan, Jun Zhang

Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions

Wei Jiang, Sifan Yang, Yibo Wang, Lijun Zhang