NeurIPS 2024

4,493 papers

Tackling Uncertain Correspondences for Multi-Modal Entity Alignment

Liyi Chen, Ying Sun, Shengzhe Zhang, Yuyang Ye, Wei Wu

Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images

Qi Song, Ziyuan Luo, Ka Chun Cheung, Simon See, Renjie Wan

Streaming Long Video Understanding with Large Language Models

Rui Qian, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Shuangrui Ding

Multiple Physics Pretraining for Spatiotemporal Surrogate Models

Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Parker, Ruben Ohana, Miles Cranmer

Fetch and Forge: Efficient Dataset Condensation for Object Detection

Ding Qi, Jian Li, Jinlong Peng, Bo Zhao, Shuguang Dou

Physically Compatible 3D Object Modeling from a Single Image

Minghao Guo, Bohan Wang, Pingchuan Ma, Tianyuan Zhang, Crystal Elaine Owens

Unlocking the Potential of Global Human Expertise

Elliot Meyerson, Olivier Francon, Darren Sargent, Babak Hodjat, Risto Miikkulainen

Optimal Transport-based Labor-free Text Prompt Modeling for Sketch Re-identification

Rui Li, Tingting Ren, Jie Wen, Jinxing Li

ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer

Jiawen Zhang, Shun Zheng, Xumeng Wen, Xiaofang Zhou, Jiang Bian

Autoregressive Policy Optimization for Constrained Allocation Tasks

David Winkel, Niklas Strauß, Maximilian Bernhard, Zongyue Li, Thomas Seidl

Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists

Joachim Baumann, Celestine Mendler-Dünner

STL: Still Tricky Logic (for System Validation, Even When Showing Your Work)

Isabelle Hurley, Rohan Paleja, Ashley Suh, Jaime D. Peña, Ho Chit Siu

LoD-Loc: Aerial Visual Localization using LoD 3D Map with Neural Wireframe Alignment

Juelin Zhu, Shen Yan, Long Wang, Shengyue Zhang, Yu Liu

Mixture of Experts Meets Prompt-Based Continual Learning

Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen, Trang Pham

Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning

Takuo Matsubara

Multi-turn Reinforcement Learning with Preference Human Feedback

Lior Shani, Aviv Rosenberg, Asaf Cassel, Oran Lang, Daniele Calandriello

Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning

Abdulkadir Çelikkanat, Andrés R. Masegosa, Thomas D. Nielsen

Retrospective for the Dynamic Sensorium Competition for predicting large-scale mouse primary visual cortex activity from videos

Polina Turishcheva, Paul G. Fahey, Michaela Vystrčilová, Laura Hansel, Rachel Froebe

Hallo3D: Multi-Modal Hallucination Detection and Mitigation for Consistent 3D Content Generation

Hongbo Wang, Jie Cao, Jin Liu, Xiaoqiang Zhou, Huaibo Huang

Derivatives of Stochastic Gradient Descent in parametric optimization

Franck Iutzeler, Edouard Pauwels, Samuel Vaiter

Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass

Ethan Shen, Alan Fan, Sarah Pratt, Jae Sung Park, Matthew Wallingford

SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers

Shraman Pramanick, Rama Chellappa, Subhashini Venugopalan

Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data

Miruna Oprescu, Nathan Kallus

Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse

Samuel Lippl, Jack Lindsey

Improving Generalization and Convergence by Enhancing Implicit Regularization

Mingze Wang, Jinbo Wang, Haotian He, Zilin Wang, Guanhua Huang

Multi-model Ensemble Conformal Prediction in Dynamic Environments

Erfan Hajihashemi, Yanning Shen

TPC: Test-time Procrustes Calibration for Diffusion-based Human Image Animation

Sunjae Yoon, Gwanhyeong Koo, Younghwan Lee, Chang D. Yoo

Unveiling the Tapestry of Consistency in Large Vision-Language Models

yuan zhang, Fei Xiao, Tao Huang, Chun-Kai Fan, Hongyuan Dong

Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates

Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal

Knowledge Circuits in Pretrained Transformers

Yunzhi Yao, Ningyu Zhang, Zekun Xi, Mengru Wang, Ziwen Xu

MambaLRP: Explaining Selective State Space Sequence Models

Farnoush Rezaei Jafari, Grégoire Montavon, Klaus-Robert Müller, Oliver Eberle

Multi-Agent Coordination via Multi-Level Communication

Ziluo Ding, Zeyuan Liu, Zhirui Fang, Kefan Su, Liwen Zhu

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation

Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy

Point-PRC: A Prompt Learning Based Regulation Framework for Generalizable Point Cloud Analysis

Hongyu Sun, Qiuhong Ke, Yongcai Wang, Wang Chen, Kang Yang

Exploring the Role of Large Language Models in Prompt Encoding for Diffusion Models

Bingqi Ma, Zhuofan Zong, Guanglu Song, hongsheng Li, Yu Liu

Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors

Zihui Wu, Yu Sun, Yifan Chen, Bingliang Zhang, Yisong Yue

Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts

Huy Nguyen, nhật Hồ, Alessandro Rinaldo

FedGMKD: An Efficient Prototype Federated Learning Framework through Knowledge Distillation and Discrepancy-Aware Aggregation

Jianqiao Zhang, Caifeng Shan, Jungong Han

Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees

Nicolas Beltran-Velez, Alessandro Antonio Grande, Achille Nazaret, Alp Kucukelbir, David Blei

SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining

Andi Han, Jiaxiang Li, Wei Huang, Mingyi Hong, Akiko Takeda

Large Language Model Unlearning via Embedding-Corrupted Prompts

Chris Yuhao Liu, Yaxuan Wang, Jeffrey Flanigan, Yang Liu

E^3: Exploring Embodied Emotion Through A Large-Scale Egocentric Video Dataset

Wang Lin, Yueying Feng, Wenkang Han, Tao Jin, Zhou Zhao

Deep Support Vectors

JunHoo Lee, Hyunho Lee, Kyomin Hwang, Nojun Kwak

Latent Diffusion for Neural Spiking Data

Jaivardhan Kapoor, Auguste Schulz, Julius Vetter, Felix Pei, Richard Gao

Data Acquisition via Experimental Design for Data Markets

Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael I. Jordan

Deep Bayesian Active Learning for Preference Modeling in Large Language Models

Luckeciano C. Melo, Panagiotis Tigas, Alessandro Abate, Yarin Gal

Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors

Anisha Pal, Julia Kruk, Mansi Phute, Manognya Bhattaram, Diyi Yang

Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance

Jinmin He, Kai Li, Yifan Zang, Haobo Fu, Qiang Fu

Code Repair with LLMs gives an Exploration-Exploitation Tradeoff

Hao Tang, Keya Hu, Jin Peng Zhou, Sicheng Zhong, Wei-Long Zheng

Regression under demographic parity constraints via unlabeled post-processing

Gayane Taturyan, Evgenii Chzhen, Mohamed Hebiri

DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models

Hengkang Wang, Xu Zhang, Taihui Li, Yuxiang Wan, Tiancong Chen

PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition

Jinghui Lu, Ziwei Yang, Yanjie Wang, Xuejing Liu, Brian Mac Namee

Robust Conformal Prediction Using Privileged Information

Shai Feldman, Yaniv Romano

Noise Contrastive Alignment of Language Models with Explicit Rewards

Huayu Chen, Guande He, Lifan Yuan, Ganqu Cui, Hang Su

Verified Safe Reinforcement Learning for Neural Network Dynamic Models

Junlin Wu, Huan Zhang, Yevgeniy Vorobeychik

Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models

Javier Gonzalez, Aditya V. Nori

State-free Reinforcement Learning

Mingyu Chen, Aldo Pacchiano, Xuezhou Zhang

QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space Model

Fei Xie, Weijia Zhang, Zhongdao Wang, Chao Ma

Oracle-Efficient Reinforcement Learning for Max Value Ensembles

Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell

Is the MMI Criterion Necessary for Interpretability? Degenerating Non-causal Features to Plain Noise for Self-Rationalization

Wei Liu, Zhiying Deng, Zhongyu Niu, Jun Wang, Haozhao Wang

InstructG2I: Synthesizing Images from Multimodal Attributed Graphs

Bowen Jin, Ziqi Pang, Bingjun Guo, Yu-Xiong Wang, Jiaxuan You

Adaptive Sampling for Efficient Softmax Approximation

Tavor Z. Baharav, Ryan Kang, Colin Sullivan, Mo Tiwari, Eric Luxenberg

Pruning neural network models for gene regulatory dynamics using data and domain knowledge

Intekhab Hossain, Jonas Fischer, Rebekka Burkholz, John Quackenbush

The Fairness-Quality Tradeoff in Clustering

Rashida Hakim, Ana-Andreea Stoica, Christos H. Papadimitriou, Mihalis Yannakakis

Truncated Variance Reduced Value Iteration

Yujia Jin, Ishani Karmarkar, Aaron Sidford, Jiayi Wang

Neural Residual Diffusion Models for Deep Scalable Vision Generation

Zhiyuan Ma, Liangliang Zhao, Biqing Qi, Bowen Zhou

Differentiable Structure Learning with Partial Orders

Taiyu Ban, Lyuzhou Chen, Xiangyu Wang, Xin Wang, Derui Lyu

SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagery

Jian Song, Hongruixuan Chen, Weihao Xuan, Junshi Xia, Naoto Yokoya

Empowering Visible-Infrared Person Re-Identification with Large Foundation Models

Zhangyi Hu, Bin Yang, Mang Ye

Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Yuxi Ren, Xin Xia, Yanzuo Lu, Jiacheng Zhang, Jie Wu

Conditional Density Estimation with Histogram Trees

Lincen Yang, Matthijs van Leeuwen

IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution

Zai-Zuo Tang, Yu-Bin Yang

Truthfulness of Calibration Measures

Nika Haghtalab, Mingda Qiao, Kunhe Yang, Eric Zhao

Navigating Extremes: Dynamic Sparsity in Large Output Spaces

Nasib Ullah, Erik Schultheis, Mike Lasby, Yani Ioannou, Rohit Babbar

In-Trajectory Inverse Reinforcement Learning: Learn Incrementally Before an Ongoing Trajectory Terminates

Shicheng Liu, Minghui Zhu

Learning Low-Rank Feature for Thorax Disease Classification

Yancheng Wang, Rajeev Goel, Utkarsh Nath, Alvin C. Silva, Teresa Wu

Reinforcement Learning with LTL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards

Xuan-Bach Le, Dominik Wagner, Leon Witzman, Alexander Rabinovich, Luke Ong

Learning Goal-Conditioned Representations for Language Reward Models

Vaskar Nath, Dylan Slack, Jeff Da, Yuntao Ma, Hugh Zhang

DropEdge not Foolproof: Effective Augmentation Method for Signed Graph Neural Networks

Zeyu Zhang, Lu Li, Shuyan Wan, Sijie Wang, Zhiyi Wang

The Impact of Initialization on LoRA Finetuning Dynamics

Soufiane Hayou, Nikhil Ghosh, Bin Yu

Conformalized Credal Set Predictors

Alireza Javanmardi, David Stutz, Eyke Hüllermeier

Focus On What Matters: Separated Models For Visual-Based RL Generalization

Di Zhang, Bowen Lv, Hai Zhang, Feifan Yang, Junqiao Zhao

Soft Superpixel Neighborhood Attention

Kent Gauen, Stanley Chan

Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network

Xiao Guo, Vishal Asnani, Sijia Liu, Xiaoming Liu

Gated Slot Attention for Efficient Linear-Time Sequence Modeling

Yu Zhang, Songlin Yang, Ruijie Zhu, Yue Zhang, Leyang Cui

OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation

Yaming Guo, Chen Zhu, Hengshu Zhu, Tieru Wu

An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models

Yunzhe Hu, Difan Zou, Dong Xu

Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning

Fei Zhou, Peng Wang, Lei Zhang, Zhenghua Chen, Wei Wei

Uncovering Safety Risks of Large Language Models through Concept Activation Vector

Zhihao Xu, Ruixuan Huang, Changyu CHEN, Xiting Wang

What type of inference is planning?

Miguel Lázaro-Gredilla, Li Yang Ku, Kevin P. Murphy, Dileep George

Dual Critic Reinforcement Learning under Partial Observability

Jinqiu Li, Enmin Zhao, Tong Wei, Junliang Xing, SHIMING XIANG

Strategic Linear Contextual Bandits

Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis, Haifeng Xu

Iterative Reasoning Preference Optimization

Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar

Label Noise: Ignorance Is Bliss

Yilun Zhu, Jianxin Zhang, Aditya Gangrade, Clayton Scott

S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning

Weihao Lin, Shengji Tang, Chong Yu, Peng Ye, Tao Chen

Understanding the Transferability of Representations via Task-Relatedness

Akshay Mehra, Yunbei Zhang, Jihun Hamm

KFNN: K-Free Nearest Neighbor For Crowdsourcing

Wenjun Zhang, Liangxiao Jiang, Chaoqun Li

RedPajama: an Open Dataset for Training Large Language Models

Maurice Weber, Daniel Y. Fu, Quentin Anthony, Yonatan Oren, Shane Adams

Efficient Graph Matching for Correlated Stochastic Block Models

Shuwen Chai, Miklós Z. Rácz

LocCa: Visual Pretraining with Location-aware Captioners

Bo Wan, Michael Tschannen, Yongqin Xian, Filip Pavetic, Ibrahim Alabdulmohsin