NeurIPS 2024

4,493 papers

Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training

Kristjan Greenewald, Yuancheng Yu, Hao Wang, Kai Xu

User-Creator Feature Polarization in Recommender Systems with Dual Influence

Tao LIN, Kun Jin, Andrew Estornell, Xiaoying Zhang, Yiling Chen

From Text to Trajectory: Exploring Complex Constraint Representation and Decomposition in Safe Reinforcement Learning

Pusen Dong, Tianchen Zhu, Yue Qiu, Haoyi Zhou, Jianxin Li

VeXKD: The Versatile Integration of Cross-Modal Fusion and Knowledge Distillation for 3D Perception

Yuzhe JI, Yijie Chen, Liuqing Yang, Rui Ding, Meng Yang

Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity

Chaoqi Chen, Luyao Tang, Hui Huang

Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups

Fengyu Gao, Ruiquan Huang, Jing Yang

IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design Patents

Homaira Huda Shomee, Zhu Wang, Sourav Medya, Sathya N. Ravi

ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization

Luca Eyring, Shyamgopal Karthik, Karsten Roth, Alexey Dosovitskiy, Zeynep Akata

Instance-adaptive Zero-shot Chain-of-Thought Prompting

Xiaosong Yuan, Chen Shen, Shaotian Yan, Xiaofeng Zhang, Liang Xie

Return of Unconditional Generation: A Self-supervised Representation Generation Method

Tianhong Li, Dina Katabi, Kaiming He

A StrongREJECT for Empty Jailbreaks

Alexandra Souly, Qingyuan Lu, Dillon Bowen, Tu Trinh, Elvis Hsieh

GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring

Dongwoo Lee, Joonkyu Park, Kyoung Mu Lee

Dynamic Rescaling for Training GNNs

Nimrah Mustafa, Rebekka Burkholz

Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations

Nicholas Gao, Stephan Günnemann

Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection

Saehyung Lee, Jisoo Mok, Sangha Park, Yongho Shin, Dahuin Jung

ResAD: A Simple Framework for Class Generalizable Anomaly Detection

Xincheng Yao, Zixin Chen, Chao Gao, Guangtao Zhai, Chongyang Zhang

Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning

Jifan Zhang, Lalit Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou

fMRI predictors based on language models of increasing complexity recover brain left lateralization

Laurent Bonnasse-Gahot, Christophe Pallier

Efficient Φ-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games

Brian Hu Zhang, Ioannis Anagnostides, Gabriele Farina, Tuomas Sandholm

Hierarchical Uncertainty Exploration via Feedforward Posterior Trees

Elias Nehme, Rotem Mulayoff, Tomer Michaeli

Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image

Kailu Wu, Fangfu Liu, Zhihan Cai, Runjie Yan, Hanyang Wang

Assembly Fuzzy Representation on Hypergraph for Open-Set 3D Object Retrieval

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

Adaptive Passive-Aggressive Framework for Online Regression with Side Information

Runhao Shi, Jiaxi Ying, Daniel P. Palomar

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation

Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards

Confidence Regulation Neurons in Language Models

Alessandro Stolfo, Ben Wu, Wes Gurnee, Yonatan Belinkov, Xingyi Song

Tolerant Algorithms for Learning with Arbitrary Covariate Shift

Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan

Open-Vocabulary Object Detection via Language Hierarchy

Jiaxing Huang, Jingyi Zhang, Kai Jiang, Shijian Lu

SpaceByte: Towards Deleting Tokenization from Large Language Modeling

Kevin Slagle

Identifying Latent State-Transition Processes for Individualized Reinforcement Learning

Yuewen Sun, Biwei Huang, Yu Yao, Donghuo Zeng, Xinshuai Dong

Almost Surely Asymptotically Constant Graph Neural Networks

Sam Adam-Day, Michael Benedikt, İsmail İlkan Ceylan, Ben Finkelshtein

A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning

Jacob Adkins, Michael Bowling, Adam White

CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial Defense

Mingkun Zhang, Keping Bi, Wei Chen, Quanrun Chen, Jiafeng Guo

On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation

Yuheng Zhang, Nan Jiang

Transductive Active Learning: Theory and Applications

Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause

A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits

Jungyhun Lee, Se-Young Yun, Kwang-Sung Jun

Distributional Successor Features Enable Zero-Shot Policy Optimization

Chuning Zhu, Xinqi Wang, Tyler Han, Simon Shaolei Du, Abhishek Gupta

EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries

Sunjun Kweon, Jiyoun Kim, Heeyoung Kwak, Dongchul Cha, Hangyul Yoon

Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation

Jiawei Wang, Renhe Jiang, Chuang Yang, Zengqing Wu, makoto onizuka

Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking

Pranav Singh Chib, Pravendra Singh

Learning Optimal Tax Design in Nonatomic Congestion Games

Qiwen Cui, Maryam Fazel, Simon S Du, Simon S. Du

ACFun: Abstract-Concrete Fusion Facial Stylization

Jiapeng Ji, Kun Wei, Ziqi Zhang, Cheng Deng

FairWire: Fair Graph Generation

O. Deniz Kose, Yanning Shen

Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformers

Lirui Wang, Xinlei Chen, Jialiang Zhao, Kaiming He

LoCo: Learning 3D Location-Consistent Image Features with a Memory-Efficient Ranking Loss

Dominik A. Kloepfer, João Henriques, Dylan Campbell

Accuracy is Not All You Need

Abhinav Dutta, Sanjeev Krishnan, Nipun Kwatra, Ramachandran Ramjee

Moving Off-the-Grid: Scene-Grounded Video Representations

Sjoerd van Steenkiste, Daniel Zoran, Yi Yang, Yulia Rubanova, Rishabh Kabra

Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment

Jiaxiang Li, Siliang Zeng, Hoi-To Wai, Chenliang Li, Alfredo Garcia

The Power of Extrapolation in Federated Learning

Hanmin Li, Kirill Acharya, Peter Richtarik

SimPO: Simple Preference Optimization with a Reference-Free Reward

Yu Meng, Mengzhou Xia, Danqi Chen

Learning-Augmented Priority Queues

Ziyad Benomar, Christian Coester

Crafting Interpretable Embeddings for Language Neuroscience by Asking LLMs Questions

Vinamra Benara, Chandan Singh, John X. Morris, Richard J. Antonello, Ion Stoica

RobIR: Robust Inverse Rendering for High-Illumination Scenes

Ziyi Yang, Yanzhen Chen, Xinyu Gao, Yazhen Yuan, Yu Wu

Robust Reinforcement Learning from Corrupted Human Feedback

Alexander Bukharin, Ilgee Hong, Haoming Jiang, Zichong Li, Qingru Zhang

LLM Dataset Inference: Did you train on my dataset?

Pratyush Maini, Hengrui Jia, Nicolas Papernot, Adam Dziedzic

Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing

Viktor Zaverkin, Francesco Alesiani, Takashi Maruyama, Federico Errica, Henrik Christiansen

Rethinking the Capacity of Graph Neural Networks for Branching Strategy

Ziang Chen, Jialin Liu, Xiaohan Chen, Xinshang Wang, Wotao Yin

Particle Semi-Implicit Variational Inference

Jen Ning Lim, Adam M. Johansen

Metric Space Magnitude for Evaluating the Diversity of Latent Representations

Katharina Limbeck, Rayna Andreeva, Rik Sarkar, Bastian Rieck

Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?

Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang

Reconstructing the Image Stitching Pipeline: Integrating Fusion and Rectangling into a Unified Inpainting Model

Ziqi Xie, Weidong Zhao, Xianhui Liu, Jian Zhao, Ning Jia

Grid4D: 4D Decomposed Hash Encoding for High-Fidelity Dynamic Gaussian Splatting

Jiawei Xu, Zexin Fan, Jian Yang, Jin Xie

Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks

Chiraag Kaushik, Justin Romberg, Vidya Muthukumar

Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements

Jiseok Chae, Chulhee Yun, Donghwan Kim

No-regret Learning in Harmonic Games: Extrapolation in the Face of Conflicting Interests

Davide Legacci, Panayotis Mertikopoulos, Christos Papadimitriou, Georgios Piliouras, Bary Pradelski

Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice

Sebastiaan De Peuter, Shibei Zhu, Yujia Guo, Andrew Howes, Samuel Kaski

Rethinking Optimal Transport in Offline Reinforcement Learning

Arip Asadulaev, Rostislav Korst, Alexander Korotin, Vage Egiazarian, Andrey Filchenkov

Subject-driven Text-to-Image Generation via Preference-based Reinforcement Learning

Yanting Miao, William Loh, Suraj Kothawade, Pascal Poupart, Abdullah Rashwan

Towards Understanding Extrapolation: a Causal Lens

Lingjing Kong, Guangyi Chen, Petar Stojanov, Haoxuan Li, Eric P. Xing

Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond

Alan Jeffares, Alicia Curth, Mihaela van der Schaar

Richelieu: Self-Evolving LLM-Based Agents for AI Diplomacy

Zhenyu Guan, Xiangyu Kong, Fangwei Zhong, Yizhou Wang

GraphTrail: Translating GNN Predictions into Human-Interpretable Logical Rules

Burouj Armgaan, Manthan Dalmia, Sourav Medya, Sayan Ranu

Persistent Test-time Adaptation in Recurring Testing Scenarios

Trung-Hieu Hoang, Duc Minh Vo, Minh N. Do

Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference

Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie

DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data

Hanyang Chen, Yang Jiang, Shengnan Guo, Xiaowei Mao, Youfang Lin

Relational Verification Leaps Forward with RABBit

Tarun Suresh, Debangshu Banerjee, Gagandeep Singh

Stochastic Optimal Control and Estimation with Multiplicative and Internal Noise

Francesco Damiani, Akiyuki Anzai, Jan Drugowitsch, Gregory C. DeAngelis, Ruben Moreno-Bote

Continuously Learning, Adapting, and Improving: A Dual-Process Approach to Autonomous Driving

Jianbiao Mei, Yukai Ma, Xuemeng Yang, Licheng Wen, Xinyu Cai

Multi-Object 3D Grounding with Dynamic Modules and Language-Informed Spatial Attention

Haomeng Zhang, Chiao-An Yang, Raymond A. Yeh

What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration

Libo Qin, Qiguang Chen, Hao Fei, Zhi Chen, Min Li

Not Just Object, But State: Compositional Incremental Learning without Forgetting

Yanyi Zhang, Binglin Qiu, Qi Jia, Yu Liu, Ran He

MotionCraft: Physics-Based Zero-Shot Video Generation

Antonio Montanaro, Luca Savant Aira, Emanuele Aiello, Diego Valsesia, Enrico Magli

UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction

Yansong Ning, Hao Liu

MetaCURL: Non-stationary Concave Utility Reinforcement Learning

Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard, Nadia Oudjane

Prospective Learning: Learning for a Dynamic Future

Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Pratik Chaudhari

SG-Bench: Evaluating LLM Safety Generalization Across Diverse Tasks and Prompt Types

Yutao Mou, Shikun Zhang, Wei Ye

DiffuLT: Diffusion for Long-tail Recognition Without External Knowledge

Jie Shao, Ke Zhu, Hanxiao Zhang, Jianxin Wu

Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization

Hongling Zheng, Li Shen, Yong Luo, Tongliang Liu, Jialie Shen

Procedure-Aware Surgical Video-language Pretraining with Hierarchical Knowledge Augmentation

Kun Yuan, Vinkle Srivastav, Nassir Navab, Nicolas Padoy

Cross-Device Collaborative Test-Time Adaptation

Guohao Chen, Shuaicheng Niu, Deyu Chen, Shuhai Zhang, Changsheng Li

IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs

Xi Gao, Jinxin Xiong, Akang Wang, Qihong Duan, Jiang Xue

Towards Neuron Attributions in Multi-Modal Large Language Models

Junfeng Fang, Zongze Bi, Ruipeng Wang, Houcheng Jiang, Yuan Gao

DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction

Qilong Ma, Haixu Wu, Lanxiang Xing, Shangchen Miao, Mingsheng Long

Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization

Xinyu Lyu, Beitao Chen, Lianli Gao, Jingkuan Song, Hengtao Shen

On the Convergence of Loss and Uncertainty-based Active Learning Algorithms

Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic

EMR-Merging: Tuning-Free High-Performance Model Merging

Chenyu Huang, Peng Ye, Tao Chen, Tong He, Xiangyu Yue

Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars

Zhaoxuan Wu, Xiaoqiang Lin, Zhongxiang Dai, Wenyang Hu, YAO SHU

On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization

Alexander Tyurin, Peter Richtarik

Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy

Shima Adeli, Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh

GLinSAT: The General Linear Satisfiability Neural Network Layer By Accelerated Gradient Descent

Hongtai Zeng, Chao Yang, Yanzhen Zhou, Cheng Yang, Qinglai Guo

DiffuserLite: Towards Real-time Diffusion Planning

Zibin Dong, Jianye Hao, Yifu Yuan, Fei Ni, Yitian Wang