NeurIPS 2024

4,493 papers

Improving the Learning Capability of Small-size Image Restoration Network by Deep Fourier Shifting

man zhou

Theoretical guarantees in KL for Diffusion Flow Matching

Marta Gentiloni Silveri, Giovanni Conforti, Alain Durmus

Truth is Universal: Robust Detection of Lies in LLMs

Lennart Bürger, Fred A. Hamprecht, Boaz Nadler

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

David Smerkous, Qinxun Bai, Li Fuxin

Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond

Yingcong Li, Ankit Singh Rawat, Samet Oymak

An Analysis of Elo Rating Systems via Markov Chains

Sam Olesker-Taylor, Luca Zanetti

Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?

Peter Súkeník, Christoph Lampert, Marco Mondelli

Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension

Kedar Karhadkar, Michael Murray, Guido Montúfar

Linear Time Approximation Algorithm for Column Subset Selection with Local Search

Yuanbin Zou, Ziyun Huang, Jinhui Xu, Jianxin Wang, Qilong Feng

Unsupervised Anomaly Detection in The Presence of Missing Values

Feng Xiao, Jicong Fan

Human Expertise in Algorithmic Prediction

Rohan Alur, Manish Raghavan, Devavrat Shah

Going Beyond Heuristics by Imposing Policy Improvement as a Constraint

Chi-Chang Lee, Zhang-Wei Hong, Pulkit Agrawal

Divergences between Language Models and Human Brains

Yuchen Zhou, Emmy Liu, Graham Neubig, Michael J. Tarr, Leila Wehbe

Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios

Shantanu Jaiswal, Debaditya Roy, Basura Fernando, Cheston Tan

InversionView: A General-Purpose Method for Reading Information from Neural Activations

Xinting Huang, Madhur Panwar, Navin Goyal, Michael Hahn

Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise

Sebastian Allmeier, Nicolas Gast

FNP: Fourier Neural Processes for Arbitrary-Resolution Data Assimilation

Kun Chen, Peng Ye, Hao Chen, Kang Chen, Tao Han

Learning the Infinitesimal Generator of Stochastic Diffusion Processes

Vladimir R. Kostic, Karim Lounici, Hélène Halconruy, Timothée Devergne, Massimiliano Pontil

Partial Transportability for Domain Generalization

Kasra Jalaldoust, Alexis Bellot, Elias Bareinboim

Diffusion Twigs with Loop Guidance for Conditional Graph Generation

Giangiacomo Mercatali, Yogesh Verma, Andre Freitas, Vikas Garg

Graph Classification via Reference Distribution Learning: Theory and Practice

Zixiao Wang, Jicong Fan

Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure

Bozhen Hu, Cheng Tan, Jun Xia, Yue Liu, Lirong Wu

Token Merging for Training-Free Semantic Binding in Text-to-Image Synthesis

Taihang Hu, Linxuan Li, Joost van de Weijer, Hongcheng Gao, Fahad Shahbaz Khan

Benchmarking Complex Instruction-Following with Multiple Constraints Composition

Bosi Wen, Pei Ke, Xiaotao Gu, Lindong Wu, Hao Huang

ProTransformer: Robustify Transformers via Plug-and-Play Paradigm

Zhichao Hou, Weizhi Gao, Yuchen Shen, Feiyi Wang, Xiaorui Liu

Transformers on Markov data: Constant depth suffices

Nived Rajaraman, Marco Bondaschi, Kannan Ramchandran, Michael Gastpar, Ashok Vardhan Makkuva

Confusion-Resistant Federated Learning via Diffusion-Based Data Harmonization on Non-IID Data

Xiaohong Chen, Canran Xiao, Yongmei Liu

Mixture of Scales: Memory-Efficient Token-Adaptive Binarization for Large Language Models

Dongwon Jo, Taesu Kim, Yulhwa Kim, Jae-Joon Kim

Linguistic Collapse: Neural Collapse in (Large) Language Models

Robert Wu, Vardan Papyan

Task-oriented Time Series Imputation Evaluation via Generalized Representers

Zhixian Wang, Linxiao Yang, Liang Sun, Qingsong Wen, Yi Wang

ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition

Mohammadreza Salehi, Jae Sung Park, Tanush Yadav, Aditya Kusupati, Ranjay Krishna

Interpreting the Weight Space of Customized Diffusion Models

Amil Dravid, Yossi Gandelsman, Kuan-Chieh Wang, Rameen Abdal, Gordon Wetzstein

EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding

Thanh-Dat Truong, Utsav Prabhu, Dongyi Wang, Bhiksha Raj, Susan Gauch

Efficient Discrepancy Testing for Learning with Distribution Shift

Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis, Konstantinos Stavropoulos, Arsen Vasilyan

Generative Modelling of Structurally Constrained Graphs

Manuel Madeira, Clément Vignac, Dorina Thanou, Pascal Frossard

Diffusion Imitation from Observation

Bo-Ruei Huang, Chun-Kai Yang, Chun-Mao Lai, Dai-Jie Wu, Shao-Hua Sun

Understanding Multi-Granularity for Open-Vocabulary Part Segmentation

Jiho Choi, Seungho Lee, Minhyun Lee, Hyunjung Shim, Seon-Ho Lee

Object segmentation from common fate: Motion energy processing enables human-like zero-shot generalization to random dot stimuli

Matthias Tangemann, Matthias Kümmerer, Matthias Bethge

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning

Jake Fawkes, Nic Fishman, Mel Andrews, Zachary C. Lipton

Towards Effective Planning Strategies for Dynamic Opinion Networks

Bharath Muppasani, Protik Nag, Vignesh Narayanan, Biplav Srivastava, Michael N. Huhns

FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making

Yangyang Yu, Zhiyuan Yao, Haohang Li, Zhiyang Deng, Yuechen Jiang

Reinforcement Learning Guided Semi-Supervised Learning

Marzi Heidari, Hanping Zhang, Yuhong Guo

Transfer Learning for Diffusion Models

Yidong Ouyang, Liyan Xie, Hongyuan Zha, Guang Cheng

Unitary Convolutions for Learning on Graphs and Groups

Bobak T. Kiani, Lukas Fesser, Melanie Weber

Unchosen Experts Can Contribute Too: Unleashing MoE Models’ Power by Self-Contrast

Chufan Shi, Cheng Yang, Xinyu Zhu, Jiahao Wang, Taiqiang Wu

Aligning LLM Agents by Learning Latent Preference from User Edits

Ge Gao, Alexey Taymanov, Eduardo Salinas, Paul Mineiro, Dipendra Misra

SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning

Huy Hoang, Tien Mai, Pradeep Varakantham

AED: Adaptable Error Detection for Few-shot Imitation Policy

Jia-Fong Yeh, Kuo-Han Hung, Pang-Chi Lo, Chi-Ming Chung, Tsung-Han Wu

Autonomous Driving with Spiking Neural Networks

Ziqing Wang, Leilani Gilpin, Jason K. Eshraghian, Ruijie Zhu, Rui-Jie Zhu

dattri: A Library for Efficient Data Attribution

Junwei Deng, Shiyuan Zhang, Shixuan Liu, Yijun Pan, Hao Huang

Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance

Haiquan Lu, Xiaotian Liu, Yefan Zhou, Qunli Li, Kurt Keutzer

Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning Framework

Zhongchao Yi, Zhengyang Zhou, Qihe Huang, Yanjiang Chen, Liheng Yu

Zero-shot Generalizable Incremental Learning for Vision-Language Object Detection

Jieren Deng, Haojian Zhang, Kun Ding, Jianhua Hu, Xingxuan Zhang

Improving Generalization in Federated Learning with Model-Data Mutual Information Regularization: A Posterior Inference Approach

Hao Zhang, Chenglin Li, Nuowen Kan, Ziyang Zheng, Wenrui Dai

SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image Classification

Benjamin Feuer, Jiawei Xu, Niv Cohen, Patrick Yubeaton, Govind Mittal

Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models

Cong Wan, Yuhang He, Xiang Song, Yihong Gong

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

Teng Li, Liwen Zhang, Youcheng Zhang, Zijun Hu, Pengcheng Pi

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

Bong Gyun Kang, Dongjun Lee, HyunGi Kim, DoHyun Chung, Sungroh Yoon

DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging

Matteo Pagliardini, Amirkeivan Mohtashami, Francois Fleuret, Martin Jaggi

Adaptive Visual Scene Understanding: Incremental Scene Graph Generation

Naitik Khandelwal, Xiao Liu, Mengmi Zhang

Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron

Christian Schmid, James M Murray, James M. Murray

Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks

Xuyuan Liu, Yinghao Cai, Qihui Yang, Yujun Yan

Efficient Policy Evaluation Across Multiple Different Experimental Datasets

Yonghan Jung, Alexis Bellot

Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation

Yihong Guo, Yixuan Wang, Yuanyuan Shi, Pan Xu, Anqi Liu

Data subsampling for Poisson regression with pth-root-link

Han Cheng Lie, Alexander Munteanu

Constructing Semantics-Aware Adversarial Examples with a Probabilistic Perspective

Andi Zhang, Mingtian Zhang, Damon Wischik

KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World Knowledge

Pengcheng Jiang, Lang Cao, Cao Xiao, Parminder Bhatia, Jimeng Sun

X-Ray: A Sequential 3D Representation For Generation

Tao Hu, Wenhang Ge, Yuyang Zhao, Gim Hee Lee

IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark

Fredrik D Johansson, Fredrik D. Johansson

Exocentric-to-Egocentric Video Generation

Jia-Wei Liu, Weijia Mao, Zhongcong XU, Jussi Keppo, Mike Zheng Shou

UniGAD: Unifying Multi-level Graph Anomaly Detection

Yiqing Lin, Jianheng Tang, Chenyi Zi, Yuan Yao, Jia Li

Fine-Tuning is Fine, if Calibrated

Zheda Mai, Arpita Chowdhury, Ping Zhang, Cheng-Hao Tu, Hong-You Chen

Refusal in Language Models Is Mediated by a Single Direction

Andy Arditi, Oscar Obeso, Aaquib Syed, Daniel Paleka, Nina Panickssery

Quality-Improved and Property-Preserved Polarimetric Imaging via Complementarily Fusing

Chu Zhou, Yixing Liu, Chao Xu, Boxin Shi

Proximal Causal Inference With Text Data

Jacob M. Chen, Rohit Bhattacharya, Katherine A. Keith

Recurrent neural network dynamical systems for biological vision

Wayne W.M. Soo, Aldo Battista, Puria Radmard, Xiao-Jing Wang

Noether's Razor: Learning Conserved Quantities

Tycho F. A. van der Ouderaa, Mark van der Wilk, Pim de Haan

DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph

Zhehao Zhang, Jiaao Chen, Diyi Yang

Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline

Dapeng Hu, Mi Luo, Jian Liang, Chuan Sheng Foo, Chuan-Sheng Foo

Motif-oriented influence maximization for viral marketing in large-scale social networks

Mingyang Zhou, Weiji Cao, Hao Liao, Rui Mao

UniIF: Unified Molecule Inverse Folding

Zhangyang Gao, Jue Wang, Cheng Tan, Lirong Wu, Yufei Huang

Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games

Fanqi Kong, Yizhe Huang, Song-chun Zhu, Siyuan Qi, Xue Feng

A Concept-Based Explainability Framework for Large Multimodal Models

Jayneel Parekh, Pegah Khayatan, Mustafa Shukor, Alasdair Newson, Matthieu Cord

3DCoMPaT200: Language Grounded Large-Scale 3D Vision Dataset for Compositional Recognition

Mahmoud Ahmed, Xiang Li, Arpit Prajapati, Mohamed Elhoseiny

Avoiding Undesired Future with Minimal Cost in Non-Stationary Environments

Wen-Bo Du, Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou

Weak Supervision Performance Evaluation via Partial Identification

Felipe Maia Polo, Subha Maity, Mikhail Yurochkin, Moulinath Banerjee, Yuekai Sun

AirSketch: Generative Motion to Sketch

Hui Xian Grace Lim, Xuanming Cui, Yogesh S Rawat, Ser Nam Lim, Ser-Nam Lim

CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities

Rohith Peddi, Shivvrat Arya, Bharath Challa, Likhitha Pallapothula, Akshay Vyas

Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization

Jiarui Jiang, Wei Huang, Miao Zhang, Taiji Suzuki, Liqiang Nie

Learning Generalized Linear Programming Value Functions

Joey Huchette, Christian Tjandraatmadja, Tu Anh Nguyen, Tu Anh-Nguyen

A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs

Haoxuan Li, Yue Liu, Zhi Geng, Kun Zhang

PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics

Sunay Bhat, Jeffrey Jiang, Omead Pooladzandi, Alexander Branch, Gregory Pottie

Evaluate then Cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering

Fangdi Wang, Jiaqi Jin, Jingtao Hu, Suyuan Liu, Xihong Yang

The Bayesian sampling in a canonical recurrent circuit with a diversity of inhibitory interneurons

Eryn Sale, Wenhao Zhang, Wen-Hao Zhang

Improving Environment Novelty Quantification for Effective Unsupervised Environment Design

Jayden Teoh, Wenjun Li, Pradeep Varakantham

Unrolled denoising networks provably learn to perform optimal Bayesian inference

Aayush Karan, Kulin Shah, Sitan Chen, Yonina C. Eldar

Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling

Wei Tang, Haifeng Xu, Ruimin Zhang, Derek Zhu

Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators

Yiyan Huang, Cheuk Hang Leung, Siyi Wang, Yijun Li, Qi Wu

Practical Bayesian Algorithm Execution via Posterior Sampling

Chu Xin Cheng, Raul Astudillo, Thomas Desautels, Yisong Yue

Benchmarking Structural Inference Methods for Interacting Dynamical Systems with Synthetic Data

Aoran Wang, Tsz Pan Tong, Andrzej Mizera, Jun Pang