NeurIPS 2024

4,493 papers

Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning

Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Felix Krahmer, Holger Rauhut

A Sober Look at the Robustness of CLIPs to Spurious Features

qizhou wang, Yong Lin, Yongqiang Chen, Ludwig Schmidt, Bo Han

Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models

Tuomas Kynkäänniemi, Miika Aittala, Tero Karras, Samuli Laine, Timo Aila

LP-3DGS: Learning to Prune 3D Gaussian Splatting

Zhaoliang Zhang, Tianchen Song, Li Yang, Cheng Peng, Rama Chellappa

Evaluating alignment between humans and neural network representations in image-based learning tasks

Can Demircan, Tankred Saanum, Leonardo Pettini, Marcel Binz, Blazej M Baczkowski

Improving Neural Network Surface Processing with Principal Curvatures

Josquin Harrison, James Benn, Maxime Sermesant

Synergistic Dual Spatial-aware Generation of Image-to-text and Text-to-image

Yu Zhao, Hao Fei, Xiangtai Li, Libo Qin, Jiayi Ji

Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators

Zekun Shi, Zheyuan Hu, Min Lin, Kenji Kawaguchi

Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks

Tianyi Zhang, Linrong Cai, Jeffrey Li, Nicholas Roberts, Neel Guha

Zipfian Whitening

Sho Yokoi, Han Bao, Hiroto Kurita, Hidetoshi Shimodaira

Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandits

Tian Huang, Shengbo Wang, Ke Li

UNIT: Unifying Image and Text Recognition in One Vision Encoder

Yi Zhu, Yanpeng Zhou, Chunwei Wang, Yang Cao, Jianhua Han

AutoTimes: Autoregressive Time Series Forecasters via Large Language Models

Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, Mingsheng Long

A Non-parametric Direct Learning Approach to Heterogeneous Treatment Effect Estimation under Unmeasured Confounding

Xinhai Zhang, Xingye Qiao

EvolveDirector: Approaching Advanced Text-to-Image Generation with Large Vision-Language Models

Rui Zhao, Hangjie Yuan, Yujie Wei, Shiwei Zhang, Yuchao Gu

Robot Policy Learning with Temporal Optimal Transport Reward

Yuwei Fu, Haichao Zhang, Di Wu, Wei Xu, Benoit Boulet

On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection

Xiufeng Song, Xiao Guo, Jiache Zhang, Qirui Li, LEI BAI

Targeted Sequential Indirect Experiment Design

Elisabeth Ailer, Niclas Dern, Jason Hartford, Niki Kilbertus

Accelerating Non-Maximum Suppression: A Graph Theory Perspective

King-Siong Si, Lu Sun, Weizhan Zhang, Tieliang Gong, Jiahao Wang

Adaptive Experimentation When You Can't Experiment

Yao Zhao, Kwang-Sung Jun, Tanner Fiez, Lalit Jain

Optimal Multi-Fidelity Best-Arm Identification

Riccardo Poiani, Rémy Degenne, Emilie Kaufmann, Alberto Maria Metelli, Marcello Restelli

Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer

Shuang Wu, Youtian Lin, FEIHU ZHANG, Yifei Zeng, Jingxi Xu

Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation

Yu Zheng, Guangming Wang, Jiuming Liu, Marc Pollefeys, Hesheng Wang

A Simple Framework for Generalization in Visual RL under Dynamic Scene Perturbations

Wonil Song, Hyesong Choi, Kwanghoon Sohn, Dongbo Min

Subsurface Scattering for Gaussian Splatting

Jan-Niklas Dihlmann, Arjun Majumdar, Andreas Engelhardt, Raphael Braun, Hendrik PA Lensch

Collaboration! Towards Robust Neural Methods for Routing Problems

Jianan Zhou, Yaoxin Wu, Zhiguang Cao, Wen Song, Jie Zhang

Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series

Ilan Naiman, Nimrod Berman, Itai Pemper, Idan Arbiv, Gal Fadlon

SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusion

Ming Dai, Lingfeng Yang, Yihao Xu, Zhenhua Feng, Wankou Yang

Learning Identifiable Factorized Causal Representations of Cellular Responses

Haiyi Mad, Romain Lopez, Kai Liu, Jan-Christian Huetter, David Richmond

The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations

Tyler LaBonte, John C. Hill, Xinchen Zhang, Vidya Muthukumar, Abhishek Kumar

No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation

Per Kristian Lehre, Shishen Lin

Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms

Chengyuan Deng, Jie Gao, Kevin Lu, Feng Luo, Hongbin Sun

Unlock the Intermittent Control Ability of Model Free Reinforcement Learning

Jiashun Liu, Jianye Hao, Xiaotian Hao, Yi Ma, YAN ZHENG

MeLLoC: Lossless Compression with High-order Mechanism Learning

Xinyue Luo, Jin Cheng, Yu Chen

CogVLM: Visual Expert for Pretrained Language Models

Weihan Wang, Qingsong Lv, Wenmeng Yu, Wenyi Hong, Ji Qi

Conformalized Time Series with Semantic Features

Baiting Chen, Zhimei Ren, Lu Cheng

Toward Semantic Gaze Target Detection

Samy Tafasca, Anshul Gupta, Victor Bros, Jean-Marc Odobez

Robust Contrastive Multi-view Clustering against Dual Noisy Correspondence

Ruiming Guo, Mouxing Yang, Yijie Lin, Xi Peng, Peng Hu

Extending Video Masked Autoencoders to 128 frames

Nitesh B. Gundavarapu, Luke Friedman, Raghav Goyal, Chaitra Hegde, Eirikur Agustsson

Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning

Tong Yang, Shicong Cen, Yuting Wei, Yuxin Chen, Yuejie Chi

RashomonGB: Analyzing the Rashomon Effect and Mitigating Predictive Multiplicity in Gradient Boosting

Hsiang Hsu, Ivan Brugere, shubham sharma, Freddy Lecue, Chun-Fu Chen

SampDetox: Black-box Backdoor Defense via Perturbation-based Sample Detoxification

Yanxin Yang, Chentao Jia, DengKe Yan, Ming Hu, Tianlin Li

Discrete Modeling via Boundary Conditional Diffusion Processes

Yuxuan Gu, Xiaocheng Feng, Lei Huang, Yingsheng Wu, Zekun Zhou

Convolutional Differentiable Logic Gate Networks

Felix Petersen, Hilde Kuehne, Christian Borgelt, Julian Welzel, Stefano Ermon

RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs

Yue Yu, Wei Ping, Zihan Liu, Boxin Wang, Jiaxuan You

Suitable is the Best: Task-Oriented Knowledge Fusion in Vulnerability Detection

Jingjing Wang, Minhuan Huang, Yuanpin Nie, Xiang Li, Qianjin Du

ANT: Adaptive Noise Schedule for Time Series Diffusion Models

Seunghan Lee, Kibok Lee, Taeyoung Park

Provably Efficient Interactive-Grounded Learning with Personalized Reward

Mengxiao Zhang, Yuheng Zhang, Haipeng Luo, Paul Mineiro

PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models

Fanxu Meng, Zhaohui Wang, Muhan Zhang

An Autoencoder-Like Nonnegative Matrix Co-Factorization for Improved Student Cognitive Modeling

Shenbao Yu, Yinghui Pan, Yifeng Zeng, Prashant Doshi, Guoquan Liu

PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation

Weiqin Yang, Jiawei Chen, Xin Xin, Sheng Zhou, Binbin Hu

Parameter Disparities Dissection for Backdoor Defense in Heterogeneous Federated Learning

Wenke Huang, Mang Ye, Zekun Shi, Guancheng Wan, He Li

EMVP: Embracing Visual Foundation Model for Visual Place Recognition with Centroid-Free Probing

Qibo Qiu, Shun Zhang, Haiming Gao, Honghui Yang, Haochao Ying

Towards a Scalable Reference-Free Evaluation of Generative Models

Azim Ospanov, Jingwei Zhang, Mohammad Jalali, Xuenan Cao, Andrej Bogdanov

Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization

Xiangxin Zhou, Dongyu Xue, Ruizhe Chen, Zaixiang Zheng, Liang Wang

Newton Informed Neural Operator for Solving Nonlinear Partial Differential Equations

Wenrui Hao, Xinliang Liu, Yahong Yang

Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning

Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok

A Synthetic Dataset for Personal Attribute Inference

Hanna Yukhymenko, Robin Staab, Mark Vero, Martin Vechev

DreamSteerer: Enhancing Source Image Conditioned Editability using Personalized Diffusion Models

Zhengyang Yu, Zhaoyuan Yang, Jing Zhang

Dimension-free Private Mean Estimation for Anisotropic Distributions

Yuval Dagan, Michael I. Jordan, Xuelin Yang, Lydia Zakynthinou, Nikita Zhivotovskiy

Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning

Adam Block, Dipendra Misra, Dylan J Foster, Dylan J. Foster

Unleashing Region Understanding in Intermediate Layers for MLLM-based Referring Expression Generation

Yaoyuan Liang, Zhuojun Cai, Jian Xu, Guanbo Huang, Yiran Wang

Learning the Latent Causal Structure for Modeling Label Noise

Yexiong Lin, Yu Yao, Tongliang Liu

EGSST: Event-based Graph Spatiotemporal Sensitive Transformer for Object Detection

Sheng Wu, Hang Sheng, Hui Feng, Bo Hu

Meaningful Learning: Enhancing Abstract Reasoning in Large Language Models via Generic Fact Guidance

Kai Xiong, Xiao Ding, Ting Liu, Bing Qin, Dongliang Xu

ZeroMark: Towards Dataset Ownership Verification without Disclosing Watermark

Junfeng Guo, Yiming Li, Ruibo Chen, Yihan Wu, Chenxi Liu

Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes

Yunyue Wei, Vincent Zhuang, Saraswati Soedarmadji, Yanan Sui

GL-NeRF: Gauss-Laguerre Quadrature Enables Training-Free NeRF Acceleration

Silong Yong, Yaqi Xie, Simon Stepputtis, Katia Sycara

Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation

Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun, Huawei Shen

EyeGraph: Modularity-aware Spatio Temporal Graph Clustering for Continuous Event-based Eye Tracking

Nuwan Bandara, Thivya Kandappu, Argha Sen, Ila Gokarn, Archan Misra

Neural P$^3$M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs

Yusong Wang, Chaoran Cheng, Shaoning Li, Yuxuan Ren, Bin Shao

Conditional Controllable Image Fusion

Bing Cao, Xingxin Xu, Pengfei Zhu, Qilong Wang, Qinghua Hu

APEBench: A Benchmark for Autoregressive Neural Emulators of PDEs

Felix Koehler, Simon Niedermayr, Rüdiger Westermann, Nils Thuerey

On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks

Paolo Pellizzoni, Till Hendrik Schulz, Dexiong Chen, Karsten Borgwardt

Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line

Eungyeup Kim, Mingjie Sun, Christina Baek, Aditi Raghunathan, J. Zico Kolter

NoiseGPT: Label Noise Detection and Rectification through Probability Curvature

Haoyu Wang, Zhuo Huang, Zhiwei Lin, Tongliang Liu

Can large language models explore in-context?

Akshay Krishnamurthy, Keegan Harris, Cyril Zhang, Aleksandrs Slivkins, Dylan J Foster

Learning from Offline Foundation Features with Tensor Augmentations

Emir Konuk, Christos Matsoukas, Moein Sorkhei, Phitchapha Lertsiravaramet, Kevin Smith

Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems

Kurt Butler, Daniel Waxman, Petar M. Djurić

Hybrid Reinforcement Learning Breaks Sample Size Barriers In Linear MDPs

Kevin Tan, Wei Fan, Yuting Wei

Conjugate Bayesian Two-step Change Point Detection for Hawkes Process

Zeyue Zhang, Xiaoling Lu, Feng Zhou

Label Delay in Online Continual Learning

Botos Csaba, Wenxuan Zhang, Matthias Müller, Mohamed Elhoseiny, Philip H.S. Torr

Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control

Huayu Chen, Kaiwen Zheng, Hang Su, Jun Zhu

AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents

Yao Fu, Dong-Ki Kim, Jaekyeom Kim, Sungryull Sohn, Lajanugen Logeswaran

Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models

Ali Behrouz, Michele Santacatterina, Ramin Zabih

OPUS: Occupancy Prediction Using a Sparse Set

Jiabao Wang, Zhaojiang Liu, Qiang Meng, Liujiang Yan, Ke Wang

Ensemble Learning for Heterogeneous Large Language Models with Deep Parallel Collaboration

Yichong Huang, Xiaocheng Feng, Baohang Li, Yang Xiang, Hui Wang

Expectile Regularization for Fast and Accurate Training of Neural Optimal Transport

Nazar Buzun, Maksim Bobrin, Dmitry V. Dylov

Most Influential Subset Selection: Challenges, Promises, and Beyond

Yuzheng Hu, Pingbang Hu, Han Zhao, Jiaqi W. Ma

Fearless Stochasticity in Expectation Propagation

Jonathan So, Richard E Turner, Richard E. Turner

Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis

Jianning Deng, Kartic Subr, Hakan Bilen

Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models

Minki Kang, Sung Ju Hwang, Gibbeum Lee, Jaewoong Cho

ALPINE: Unveiling The Planning Capability of Autoregressive Learning in Language Models

Siwei Wang, Yifei Shen, Shi Feng, Haoran Sun, Shang-Hua Teng

InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory

Chaojun Xiao, Pengle Zhang, Xu Han, Guangxuan Xiao, Yankai Lin

Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies

Yipu Chen, Haotian Xue, Yongxin Chen

How Transformers Utilize Multi-Head Attention in In-Context Learning? A Case Study on Sparse Linear Regression

Xingwu Chen, lei zhao, Difan Zou

Learning diverse causally emergent representations from time series data

David McSharry, Christos Kaplanis, Fernando E. Rosas, Pedro A.M Mediano, Pedro A.M. Mediano

MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs

Zhongshen Zeng, Yinhong Liu, Yingjia Wan, Jingyao Li, Pengguang Chen

Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment

JIAWEI DU, Xin Zhang, Juncheng Hu, Wenxing Huang, Joey Tianyi Zhou

Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions

Heng Li, Minghan Li, Zhi-Qi Cheng, Yifei Dong, Yuxuan Zhou