NeurIPS 2024

4,493 papers

Streaming Detection of Queried Event Start

Cristobal Eyzaguirre, Eric Tang, Shyamal Buch, Adrien Gaidon, Jiajun Wu

Adaptive Proximal Gradient Method for Convex Optimization

Yura Malitsky, Konstantin Mishchenko

SustainDC: Benchmarking for Sustainable Data Center Control

Avisek Naug, Antonio Guillen, Ricardo Luna, Vineet Gundecha, Cullen Bash

Geometry of naturalistic object representations in recurrent neural network models of working memory

Xiaoxuan Lei, Takuya Ito, Pouya Bashivan

Sample-Efficient Agnostic Boosting

Udaya Ghai, Karan Singh

Resolving Discrepancies in Compute-Optimal Scaling of Language Models

Tomer Porian, Mitchell Wortsman, Jenia Jitsev, Ludwig Schmidt, Yair Carmon

Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making

Manling Li, Shiyu Zhao, Qineng Wang, Kangrui Wang, Yu Zhou

Boosting Transferability and Discriminability for Time Series Domain Adaptation

Mingyang Liu, Xinyang Chen, Yang Shu, Xiucheng Li, Weili Guan

DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarios

Junchao Wu, Runzhe Zhan, Derek F. Wong, Shu Yang, Xinyi Yang

Lever LM: Configuring In-Context Sequence to Lever Large Vision Language Models

Xu Yang, Yingzhe Peng, Haoxuan Ma, Shuo Xu, Chi Zhang

Aligner-Encoders: Self-Attention Transformers Can Be Self-Transducers

Adam Stooke, Rohit Prabhavalkar, Khe Chai Sim, Pedro Moreno Mengibar

CoVoMix: Advancing Zero-Shot Speech Generation for Human-like Multi-talker Conversations

Leying Zhang, Yao Qian, Long Zhou, Shujie LIU, Dongmei Wang

Is O(log N) practical? Near-Equivalence Between Delay Robustness and Bounded Regret in Bandits and RL

Enoch H. Kang, P. R. Kumar

Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems

Francisco Acosta, Fatih Dinc, William T. Redman, Manu Madhav, David Klindt

QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Pashmina Cameron

HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection

Yuxin Wang, Duanyu Feng, Yongfu Dai, Zhengyu Chen, Jimin Huang

A theoretical design of concept sets: improving the predictability of concept bottleneck models

Max Ruiz Luyten, Mihaela van der Schaar

Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning

Arko Banerjee, Kia Rahmani, Joydeep Biswas, Isil Dillig

On the Complexity of Identification in Linear Structural Causal Models

Julian Dörfler, Benito van der Zander, Markus Bläser, Maciej Liśkiewicz

Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions

Jie Wang, Tingfa Xu, Lihe Ding, Jianan Li

Robust Mixture Learning when Outliers Overwhelm Small Groups

Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov

Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss for Skillful Precipitation Nowcasting

Chiu-Wai Yan, Shi Quan Foo, Van Hoan Trinh, Dit-Yan Yeung, Ka-Hing Wong

Explanations that reveal all through the deﬁnition of encoding

Aahlad Puli, Nhi Nguyen, Rajesh Ranganath

Enhancing vision-language models for medical imaging: bridging the 3D gap with innovative slice selection

Yuli Wang, Jian Peng, Yuwei Dai, Craig Jones, Haris Sair

Relating Hopfield Networks to Episodic Control

Hugo Chateau-Laurent, Frédéric Alexandre

DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos

Linhan Wang, Kai Cheng, Shuo Lei, Shengkun Wang, Wei Yin

Can an AI Agent Safely Run a Government? Existence of Probably Approximately Aligned Policies

Frédéric Berdoz, Roger Wattenhofer

OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning

Shengjie Niu, Lifan Lin, Jian Huang, Chao Wang

Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing

Yixin Ren, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou

Why Go Full? Elevating Federated Learning Through Partial Network Updates

Haolin Wang, Xuefeng Liu, Jianwei Niu, Wenkai Guo, Shaojie Tang

Stabilized Proximal-Point Methods for Federated Optimization

Xiaowen Jiang, Anton Rodomanov, Sebastian U Stich, Sebastian U. Stich

Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification

Jiangming Shi, Xiangbo Yin, Yachao Zhang, Zhizhong Zhang, Yuan Xie

Fair Kernel K-Means: from Single Kernel to Multiple Kernel

Peng Zhou, Rongwen Li, Liang Du

Efficient Prompt Optimization Through the Lens of Best Arm Identification

Chengshuai Shi, Kun Yang, Zihan Chen, Jundong Li, Jing Yang

Human-3Diffusion: Realistic Avatar Creation via Explicit 3D Consistent Diffusion Models

Yuxuan Xue, Xianghui Xie, Riccardo Marin, Gerard Pons-Moll

Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity

Qian Yu, Yining Wang, Baihe Huang, Qi Lei, Jason D. Lee

Length Optimization in Conformal Prediction

Shayan Kiyani, George Pappas, Hamed Hassani

DeNetDM: Debiasing by Network Depth Modulation

Silpa Vadakkeeveetil Sreelatha, Adarsh Kappiyath, ABHRA CHAUDHURI, Anjan Dutta

Scalable Kernel Inverse Optimization

Youyuan Long, Tolga Ok, Pedro Zattoni Scroccaro, Peyman Mohajerin Esfahani

How to Solve Contextual Goal-Oriented Problems with Offline Datasets?

Ying Fan, Jingling Li, Adith Swaminathan, Aditya Modi, Ching-An Cheng

Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need

Xianlong Wang, Minghui Li, Wei Liu, Hangtao Zhang, Shengshan Hu

SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning

Yexiao He, Ziyao Wang, Zheyu Shen, Guoheng Sun, Yucong Dai

PaCE: Parsimonious Concept Engineering for Large Language Models

Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan, Darshan Thaker, Aditya Chattopadhyay

PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models

Lemei Zhang, Peng Liu, Marcus Tiedemann Oekland Henriksboe, Even W. Lauvrak, Jon Atle Gulla

MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing

Chenjie Cao, Chaohui Yu, Fan Wang, Xiangyang Xue, Yanwei Fu

Make-it-Real: Unleashing Large Multimodal Model for Painting 3D Objects with Realistic Materials

Ye Fang, Zeyi Sun, Tong Wu, Jiaqi Wang, Ziwei Liu

ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence

Wenjie Mei, Dongzhe Zheng, Shihua Li

Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework

Zhihai Wang, Jie Wang, Qingyue Yang, Yinqi Bai, Xing Li

Elucidating the Design Space of Dataset Condensation

Shitong Shao, Zikai Zhou, Huanran Chen, Zhiqiang Shen

ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Field

Kiyohiro Nakayama, Mikaela Angelina Uy, Yang You, Ke Li, Leonida J. Guibas

CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence

Chaochao Chen, Jiaming Zhang, Yizhao Zhang, Li Zhang, Lingjuan Lyu

Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits

Zhan Yu, Qiuhao Chen, Yuling Jiao, Yinan Li, Xiliang Lu

ALI-Agent: Assessing LLMs' Alignment with Human Values via Agent-based Evaluation

Jingnan Zheng, Han Wang, An Zhang, Tai D. Nguyen, Jun Sun

Sample-Efficient Private Learning of Mixtures of Gaussians

Hassan Ashtiani, Mahbod Majid, Shyam Narayanan

Can neural operators always be continuously discretized?

Takashi Furuya, Michael Puthawala, Maarten V. de Hoop, Matti Lassas

Hierarchy-Agnostic Unsupervised Segmentation: Parsing Semantic Image Structure

Simone Rossetti, Fiora Pirri

Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning

Ruoqi Zhang, Ziwei Luo, Jens Sjölund, Per Mattsson, Thomas B Schön

An Equivalence Between Static and Dynamic Regret Minimization

Andrew Jacobsen, Francesco Orabona

Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning

Liyuan Mao, Haoran Xu, Xianyuan Zhan, Weinan Zhang, Amy Zhang

Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts

Sukwon Yun, Inyoung Choi, Jie Peng, Yangfan Wu, Jingxuan Bao

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data

Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller, Frank Hutter

Di^2Pose: Discrete Diffusion Model for Occluded 3D Human Pose Estimation

Weiquan Wang, Jun Xiao, Chunping Wang, Wei Liu, Zhao Wang

Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression

Deqing Fu, Robin Jia, Vatsal Sharan, Tianqi Chen, Tian-Qi Chen

Membership Inference Attacks against Large Vision-Language Models

Zhan Li, Yongtao Wu, Yihang Chen, Francesco Tonin, Elias Abad Rocamora

Uncovering the Redundancy in Graph Self-supervised Learning Models

Zhibiao Wang, Xiao Wang, Haoyue Deng, Nian Liu, Shirui Pan

On the Efficiency of ERM in Feature Learning

Ayoub El Hanchi, Chris J Maddison, Murat A Erdogdu, Chris J. Maddison, Murat A. Erdogdu

Dual Cone Gradient Descent for Training Physics-Informed Neural Networks

Youngsik Hwang, Dong-Young Lim

SuperDeepFool: a new fast and accurate minimal adversarial attack

Alireza Abdollahpoorrostam, Mahed Abroshan, Seyed-Mohsen Moosavi-Dezfooli

Physics-Informed Variational State-Space Gaussian Processes

Oliver Hamelijnck, Arno Solin, Theodoros Damoulas

Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation

Yunnan Wang, Ziqiang Li, Wenyao Zhang, Zequn Zhang, Baao Xie

Few-Shot Task Learning through Inverse Generative Modeling

Aviv Netanyahu, Yilun Du, Antonia Bronars, Jyothish Pari, Joshua Tenenbaum

TransAgent: Transfer Vision-Language Foundation Models with Heterogeneous Agent Collaboration

Yiwei Guo, Shaobin Zhuang, Kunchang Li, Yu Qiao, Yali Wang

Scale-invariant Optimal Sampling for Rare-events Data and Sparse Models

Jing Wang, HaiYing Wang, Hao Helen Zhang

A Modular Conditional Diffusion Framework for Image Reconstruction

Magauiya Zhussip, Iaroslav Koshelev, Stamatis Lefkimmiatis

AP-Adapter: Improving Generalization of Automatic Prompts on Unseen Text-to-Image Diffusion Models

Yuchen Fu, Zhiwei Jiang, Yuliang Liu, Cong Wang, Zexuan Deng

DDK: Distilling Domain Knowledge for Efficient Large Language Models

Jiaheng Liu, Chenchen Zhang, Jinyang Guo, Yuanxing Zhang, Haoran Que

Stopping Bayesian Optimization with Probabilistic Regret Bounds

James T. Wilson

RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

Zhuoran jin, Pengfei Cao, Chenhao Wang, Zhitao He, Hongbang Yuan

MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures

Jinjie Ni, Fuzhao Xue, Xiang Yue, Yuntian Deng, Mahir Shah

Statistical Multicriteria Benchmarking via the GSD-Front

Christoph Jansen, Georg Schollmeyer, Julian Rodemann, Hannah Blocher, Thomas Augustin

Transformers need glasses! Information over-squashing in language tasks

Federico Barbero, Andrea Banino, Steven Kapturowski, Dharshan Kumaran, João G.M. Araújo

Neuro-Vision to Language: Enhancing Brain Recording-based Visual Reconstruction and Language Interaction

Guobin Shen, Dongcheng Zhao, Xiang He, Linghao Feng, Yiting Dong

Understanding Transformers via N-Gram Statistics

Timothy Nguyen

Einsum Benchmark: Enabling the Development of Next-Generation Tensor Execution Engines

Mark Blacher, Christoph Staudt, Julien Klaus, Maurice Wenig, Niklas Merk

Do LLMs Build World Representations? Probing Through the Lens of State Abstraction

Zichao Li, Yanshuai Cao, Jackie C.K. Cheung

Learning-Augmented Algorithms with Explicit Predictors

Marek Elias, Haim Kaplan, Yishay Mansour, Shay Moran

Extracting Training Data from Molecular Pre-trained Models

Renhong Huang, Jiarong Xu, Zhiming Yang, Xiang Si, Xin Jiang

Benchmarking the Attribution Quality of Vision Models

Robin Hesse, Simone Schaub-Meyer, Stefan Roth

Statistical-Computational Trade-offs for Density Estimation

Anders Aamand, Alexandr Andoni, Justin Y. Chen, Piotr Indyk, Shyam Narayanan

Semi-supervised Multi-label Learning with Balanced Binary Angular Margin Loss

Ximing Li, Silong Liang, Changchun Li, pengfei wang, Fangming Gu

Real-world Image Dehazing with Coherence-based Pseudo Labeling and Cooperative Unfolding Network

Chengyu Fang, Chunming He, Fengyang Xiao, Yulun Zhang, Longxiang Tang

A Taxonomy of Challenges to Curating Fair Datasets

Dora Zhao, Morgan Klaus Scheuerman, Pooja Chitre, Jerone T. A. Andrews, Georgia Panagiotidou

SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection

Liangxin Liu, Xuebo Liu, Derek F. Wong, Dongfang Li, Ziyi Wang

AID: Attention Interpolation of Text-to-Image Diffusion

Qiyuan He, Jinghao Wang, Ziwei Liu, Angela Yao

Dueling over Dessert, Mastering the Art of Repeated Cake Cutting

Simina Branzei, MohammadTaghi Hajiaghayi, Reed Phillips, Suho Shin, Kun Wang

SCube: Instant Large-Scale Scene Reconstruction using VoxSplats

Xuanchi Ren, Yifan Lu, hanxue liang, Zhangjie Wu, huan ling

Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification

Yuankai Luo, Lei Shi, Xiao-ming Wu

CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training

David Brandfonbrener, Hanlin Zhang, Andreas Kirsch, Jonathan Richard Schwarz, Sham Kakade

Diffusion-based Curriculum Reinforcement Learning

Erdi Sayar, Giovanni Iacca, Ozgur S. Oguz, Alois Knoll

Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks

Wenlin Chen, Hong Ge