NeurIPS 2024

4,493 papers

Learning Versatile Skills with Curriculum Masking

Yao Tang, Zhihui Xie, Zichuan Lin, Deheng Ye, Shuai Li

Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning

Huancheng Chen, Haris Vikalo

CoFie: Learning Compact Neural Surface Representations with Coordinate Fields

Hanwen Jiang, Haitao Yang, Georgios Pavlakos, Qixing Huang

Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity

Vahid Balazadeh, Keertana Chidambaram, Viet Nguyen, Vasilis Syrgkanis, Rahul G Krishnan

Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation

Jiaming Lv, Haoyuan Yang, Peihua Li

Beyond Optimism: Exploration With Partially Observable Rewards

Simone Parisi, Alireza Kazemipour, Michael Bowling

LaSCal: Label-Shift Calibration without target labels

Teodora Popordanoska, Gorjan Radevski, Tinne Tuytelaars, Matthew B. Blaschko

Listenable Maps for Zero-Shot Audio Classifiers

Francesco Paissan, Luca Della Libera, Mirco Ravanelli, Cem Subakan

The Limits of Differential Privacy in Online Learning

Bo Li, Wei Wang, Peng Ye

Symmetry-Informed Governing Equation Discovery

Jianke Yang, Wang Rao, Nima Dehmamy, Robin Walters, Rose Yu

A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers

Ye He, Alireza Mousavi-Hosseini, Krishnakumar Balasubramanian, Murat A Erdogdu, Murat A. Erdogdu

Robust group and simultaneous inferences for high-dimensional single index model

Weichao Yang, Hongwei Shi, Xu Guo, Changliang Zou

CulturePark: Boosting Cross-cultural Understanding in Large Language Models

Cheng Li, Damien Teney, Linyi Yang, Qingsong Wen, Xing Xie

Microstructures and Accuracy of Graph Recall by Large Language Models

Yanbang Wang, Hejie Cui, Jon Kleinberg

AsCAN: Asymmetric Convolution-Attention Networks for Efficient Recognition and Generation

Anil Kag, Huseyin Coskun, Jierun Chen, Junli Cao, Willi Menapace

Learning Structure-Aware Representations of Dependent Types

Konstantinos Kogkalidis, Orestis Melkonian, Jean-Philippe Bernardy

Safe LoRA: The Silver Lining of Reducing Safety Risks when Finetuning Large Language Models

Chia-Yi Hsu, Yu-Lin Tsai, Chih-Hsun Lin, Pin-Yu Chen, Chia-Mu Yu

Dynamic Neural Regeneration: Enhancing Deep Learning Generalization on Small Datasets

Vijaya Raghavan T Ramkumar, Elahe Arani, Bahram Zonooz

Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz

Ge Yan, Mengfei Ran, Ruocheng Wang, Kaiseng Pan, Junchi Yan

LoTLIP: Improving Language-Image Pre-training for Long Text Understanding

Wei Wu, Kecheng Zheng, Shuailei Ma, Fan Lu, Yuxin Guo

Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning

Seonghyun Ban, Heesan Kong, Kee-eung Kim

Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems

Rohan Paleja, Michael Munje, Kimberlee Chestnut Chang, Reed Jensen, Mathew Gombolay

LLM-AutoDA: Large Language Model-Driven Automatic Data Augmentation for Long-tailed Problems

Pengkun Wang, Zhe Zhao, Haibin Wen, Fanfu Wang, Binwu Wang

Co-occurrence is not Factual Association in Language Models

Xiao Zhang, Miao Li, Ji Wu

Federated Graph Learning for Cross-Domain Recommendation

Ziqi Yang, Zhaopeng Peng, Zihui Wang, Jianzhong Qi, Chaochao Chen

Optimization Can Learn Johnson Lindenstrauss Embeddings

Nikos Tsikouras, Constantine Caramanis, Christos Tzamos

Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs

Xinyi Hu, Jasper C.H. Lee, Jimmy H.M. Lee, Peter J. Stuckey

A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding

Yitong Dong, Yijin Li, Zhaoyang Huang, Weikang Bian, Jingbo Liu

ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Dan Zhang, Sining Zhoubian, Ziniu Hu, Yisong Yue, Yuxiao Dong

Faster Neighborhood Attention: Reducing the O(n^2) Cost of Self Attention at the Threadblock Level

Ali Hassani, Wen-Mei Hwu, Humphrey Shi

CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset

Akshatha Arodi, Margaux Luck, Jean-Luc Bedwani, Aldo Zaimi, Ge Li

Queueing Matching Bandits with Preference Feedback

Jung-hun Kim, Min-hwan Oh

DCDepth: Progressive Monocular Depth Estimation in Discrete Cosine Domain

Kun Wang, Zhiqiang Yan, Junkai Fan, Wanlu Zhu, Xiang Li

Drones Help Drones: A Collaborative Framework for Multi-Drone Object Trajectory Prediction and Beyond

Zhechao Wang, Peirui Cheng, Mingxin Chen, Pengju Tian, Zhirui Wang

SearchLVLMs: A Plug-and-Play Framework for Augmenting Large Vision-Language Models by Searching Up-to-Date Internet Knowledge

Chuanhao Li, Zhen Li, Chenchen Jing, Shuo Liu, Wenqi Shao

Reinforcement Learning with Lookahead Information

Nadav Merlis

Stochastic contextual bandits with graph feedback: from independence number to MAS number

Yuxiao Wen, Yanjun Han, Zhengyuan Zhou

HEALNet: Multimodal Fusion for Heterogeneous Biomedical Data

Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik

Learning Distinguishable Trajectory Representation with Contrastive Loss

Tianxu Li, Kun Zhu, Juan Li, Yang Zhang

Map It Anywhere: Empowering BEV Map Prediction using Large-scale Public Datasets

Cherie Ho, Jiaye Zou, Omar Alama, Sai Mitheran Jagadesh Kumar, Benjamin Chiang

Memory-Efficient LLM Training with Online Subspace Descent

Kaizhao Liang, Bo Liu, Lizhang Chen, Qiang Liu

Flipping-based Policy for Chance-Constrained Markov Decision Processes

Xun Shen, Shuo Jiang, Akifumi Wachi, Kazumune Hashimoto, Sebastien Gros

Paloma: A Benchmark for Evaluating Language Model Fit

Ian Magnusson, Akshita Bhagia, Valentin Hofmann, Luca Soldaini, Ananya Harsh Jha

Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images

Junxian Wu, Xinyi Ke, Xiaoming Jiang, Huanwen Wu, Youyong Kong

The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains

Ezra Edelman, Nikolaos Tsilivis, Benjamin L. Edelman, Eran Malach, Surbhi Goel

Fight Back Against Jailbreaking via Prompt Adversarial Tuning

Yichuan Mo, Yuji Wang, Zeming Wei, Yisen Wang

The Sample Complexity of Gradient Descent in Stochastic Convex Optimization

Roi Livni, Amir, Koren, Livni, Schliserman

MO-DDN: A Coarse-to-Fine Attribute-based Exploration Agent for Multi-Object Demand-driven Navigation

Hongcheng Wang, Peiqi Liu, Wenzhe Cai, Mingdong Wu, Zhengyu Qian

SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion

Lu Han, Han-Jia Ye, De-Chuan Zhan, Xuyang Chen, Xu-Yang Chen

BMRS: Bayesian Model Reduction for Structured Pruning

Dustin Wright, Christian Igel, Raghavendra Selvan

Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs

Rudolf Laine, Bilal Chughtai, Jan Betley, Kaivalya Hariharan, Jérémy Scheurer

SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction

Zhihao Yu, Xu Chu, Yujie Jin, Yasha Wang, Junfeng Zhao

Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming

Lorenzo Orecchia, Jiawei Hu, Xue He, Zhe Wang, Xulei Yang

ReFT: Representation Finetuning for Language Models

Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atticus Geiger, Dan Jurafsky

Noise-Aware Differentially Private Regression via Meta-Learning

Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel P. Bruinsma, Marlon Tobaben

T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models

yibo miao, Yifan Zhu, Lijia Yu, Jun Zhu, Xiao-Shan Gao

Provable Partially Observable Reinforcement Learning with Privileged Information

Yang Cai, Xiangyu Liu, Argyris Oikonomou, Kaiqing Zhang

SurgicAI: A Hierarchical Platform for Fine-Grained Surgical Policy Learning and Benchmarking

Jin Wu, Haoying Zhou, Peter Kazanzides, Adnan Munawar, Anqi Liu

Generalizable Implicit Motion Modeling for Video Frame Interpolation

Zujin Guo, Wei Li, Chen Change Loy

Adversarial Environment Design via Regret-Guided Diffusion Models

Hojun Chung, Junseo Lee, Minsoo Kim, Dohyeong Kim, Songhwai Oh

Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters

Yifei Xia, Fangcheng Fu, Wentao Zhang, Jiawei Jiang, Bin CUI

When to Sense and Control? A Time-adaptive Approach for Continuous-Time RL

Lenart Treven, Bhavya Sukhija, Yarden As, Florian Dorfler, Andreas Krause

Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models

Hui-Po Wang, Mario Fritz

ODGEN: Domain-specific Object Detection Data Generation with Diffusion Models

Jingyuan Zhu, Shiyu Li, YuXuan Liu, Jian Yuan, Ping Huang

Alignment for Honesty

Yuqing Yang, Ethan Chern, Xipeng Qiu, Graham Neubig, Pengfei Liu

Conformal Inverse Optimization

Bo Lin, Erick Delage, Timothy C. Y. Chan

Self-Retrieval: End-to-End Information Retrieval with One Large Language Model

Qiaoyu Tang, Jiawei Chen, Zhuoqun Li, Bowen Yu, Yaojie Lu

Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity

Jikai Jin, Vasilis Syrgkanis

Fourier-enhanced Implicit Neural Fusion Network for Multispectral and Hyperspectral Image Fusion

Yu-Jie Liang, Zihan Cao, Shangqi Deng, Hong-Xia Dou, Liang-Jian Deng

Differentially Private Optimization with Sparse Gradients

Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi

Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning

Dake Bu, Wei Huang, Andi Han, Atsushi Nitanda, Taiji Suzuki

Unscrambling disease progression at scale: fast inference of event permutations with optimal transport

Peter A. Wijeratne, Daniel C. Alexander

ScaleKD: Strong Vision Transformers Could Be Excellent Teachers

Jiawei Fan, CHAO LI, Xiaolong Liu, Anbang Yao

Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning

Grzegorz Rypeść, Sebastian Cygert, Tomasz Trzcinski, Bartłomiej Twardowski

Semi-Open 3D Object Retrieval via Hierarchical Equilibrium on Hypergraph

Yang Xu, Yifan Feng, Jun Zhang, Jun-Hai Yong, Yue Gao

CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy

Jiakai Zhang, Qihe Chen, Yan Zeng, Wenyuan Gao, Xuming He

Distributional Reinforcement Learning with Regularized Wasserstein Loss

Ke Sun, yingnan zhao, Wulong Liu, Bei Jiang, Linglong Kong

Score-based generative models are provably robust: an uncertainty quantification perspective

Nikiforos Mimikos-Stamatopoulos, Benjamin J. Zhang, Markos A. Katsoulakis

A robust inlier identification algorithm for point cloud registration via ℓ_0-minimization

Yinuo Jiang, Xiuchuan Tang, cheng cheng, Ye Yuan

JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images

Zhecan Wang, Junzhang Liu, Chia-Wei Tang, Hani Alomari, Anushka Sivakumar

Improving the Training of Rectified Flows

Sangyun Lee, Zinan Lin, Giulia Fanti

UGC: Universal Graph Coarsening

Mohit Kataria, Sandeep Kumar, Jayadeva

The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

Anya Sims, Cong Lu, Jakob N. Foerster, Yee Whye Teh

Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy

Cameron Allen, Aaron Kirtland, Ruo Yu Tao, Sam Lobel, Daniel Scott

SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization

Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang, Kun Yuan

A Cross-Domain Benchmark for Active Learning

Thorben Werner, Johannes Burchert, Maximilian Stubbemann, Lars Schmidt-Thieme

SelfCodeAlign: Self-Alignment for Code Generation

Yuxiang Wei, Federico Cassano, Yifeng Ding, Naman Jain, Zachary Mueller

B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable

Shreyash Arya, Sukrut Rao, Moritz Böhle, Bernt Schiele

PTQ4DiT: Post-training Quantization for Diffusion Transformers

Junyi Wu, Haoxuan Wang, Yuzhang Shang, Mubarak Shah, Yan Yan

Are Large Language Models Good Statisticians?

Yizhang Zhu, Shiyin Du, Boyan Li, Yuyu Luo, Nan Tang

SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams

Kang Chen, Shiyan Chen, Jiyuan Zhang, Baoyue Zhang, Yajing Zheng

The ALCHEmist: Automated Labeling 500x CHEaper than LLM Data Annotators

Tzu-Heng Huang, Catherine Cao, Vaishnavi Bhargava, Frederic Sala

Induced Model Matching: Restricted Models Help Train Full-Featured Models

Usama Muneeb, Mesrob I Ohannessian, Mesrob I. Ohannessian

The Closeness of In-Context Learning and Weight Shifting for Softmax Regression

Shuai Li, Zhao Song, Yu Xia, Tong Yu, Tianyi Zhou

SGLang: Efficient Execution of Structured Language Model Programs

Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Chuyue Sun, Jeff Huang

An Analysis of Tokenization: Transformers under Markov Data

Nived Rajaraman, Jiantao Jiao, Kannan Ramchandran

BendVLM: Test-Time Debiasing of Vision-Language Embeddings

Walter Gerych, Haoran Zhang, Kimia Hamidieh, Eileen Pan, Maanas Sharma

Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch

Malek Mechergui, Sarath Sreedharan

The Mamba in the Llama: Distilling and Accelerating Hybrid Models

Junxiong Wang, Daniele Paliotta, Avner May, Alexander M. Rush, Tri Dao

HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation

Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates