NeurIPS 2024

4,493 papers

ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users

Guanlin Li, Kangjie Chen, Shudong Zhang, Jie Zhang, Tianwei Zhang

Graph Learning for Numeric Planning

Dillon Z. Chen, Sylvie Thiébaux

Lips Are Lying: Spotting the Temporal Inconsistency between Audio and Visual in Lip-Syncing DeepFakes

Weifeng Liu, Tianyi She, Boheng Li, Dongyu Yao, Ziyou Liang

A Generative Model of Symmetry Transformations

James Urquhart Allingham, Bruno Kacper Mlodozeniec, Shreyas Padhy, Javier Antoran, David Krueger

Near-Optimality of Contrastive Divergence Algorithms

Pierre Glaser, Kevin Han Huang, Arthur Gretton

Rethinking 3D Convolution in ℓ_p-norm Space

Li Zhang, Yan Zhong, Jianan Wang, Zhe Min, Rujing Wang

The Space Complexity of Approximating Logistic Loss

Gregory Dexter, Petros Drineas, Rajiv Khanna

On the Adversarial Robustness of Benjamini Hochberg

Louis L Chen, Roberto Szechtman, Matan Seri

Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization

Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang

On provable privacy vulnerabilities of graph representations

Ruofan Wu, Guanhua Fang, Mingyang Zhang, Qiying Pan, Tengfei LIU

Aligner: Efficient Alignment by Learning to Correct

Jiaming Ji, Boyuan Chen, Hantao Lou, Donghai Hong, Borong Zhang

Stochastic Newton Proximal Extragradient Method

Ruichen Jiang, Michał Dereziński, Aryan Mokhtari

Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust

Hongjie Chen, Jingqiu Ding, Yiding Hua, David Steurer

Gradient Guidance for Diffusion Models: An Optimization Perspective

Yingqing Guo, Hui Yuan, Yukang Yang, Minshuo Chen, Mengdi Wang

Imitating Language via Scalable Inverse Reinforcement Learning

Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein

A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis

Yue Yang, Mona Gandhi, Yufei Wang, Yifan Wu, Michael S. Yao

DACO: Towards Application-Driven and Comprehensive Data Analysis via Code Generation

Xueqing Wu, Rui Zheng, Jingzhen Sha, Te-Lin Wu, Hanyu Zhou

MAmmoTH2: Scaling Instructions from the Web

Xiang Yue, Tuney Zheng, Ge Zhang, Wenhu Chen

AMBROSIA: A Benchmark for Parsing Ambiguous Questions into Database Queries

Irina Saparina, Mirella Lapata

DeTrack: In-model Latent Denoising Learning for Visual Object Tracking

Xinyu Zhou, Jinglun Li, Lingyi Hong, Kaixun Jiang, Pinxue Guo

The Intelligible and Effective Graph Neural Additive Network

Maya Bechler-Speicher, Amir Globerson, Ran Gilad-Bachrach

GRANOLA: Adaptive Normalization for Graph Neural Networks

Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron

Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics

Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael Jordan, Jiantao Jiao

Binary Search with Distributional Predictions

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Aidin Niaparast

ENAT: Rethinking Spatial-temporal Interactions in Token-based Image Synthesis

Zanlin Ni, Yulin Wang, Renping Zhou, Yizeng Han, Jiayi Guo

Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy

Zeki Kazan, Jerome P. Reiter

CYCLO: Cyclic Graph Transformer Approach to Multi-Object Relationship Modeling in Aerial Videos

Trong-Thuan Nguyen, Pha Nguyen, Xin Li, Jackson Cothren, Alper Yilmaz

D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models

Haoran Que, Jiaheng Liu, Ge Zhang, Chenchen Zhang, Xingwei Qu

Mind's Eye of LLMs: Visualization-of-Thought Elicits Spatial Reasoning in Large Language Models

Wenshan Wu, Shaoguang Mao, Yadong Zhang, Yan Xia, Li Dong

Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control

Jinzhu Luo, Dingyang Chen, Qi Zhang

Continuous Product Graph Neural Networks

Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo

Immiscible Diffusion: Accelerating Diffusion Training with Noise Assignment

Yiheng Li, Heyang Jiang, Akio Kodaira, Masayoshi Tomizuka, Kurt Keutzer

Low Precision Local Training is Enough for Federated Learning

Zhiwei Li, Yiqiu Li, Binbin Lin, Zhongming Jin, Weizhong Zhang

Optimal Design for Human Preference Elicitation

Subhojyoti Mukherjee, Anusha Lalitha, Kousha Kalantari, Aniket Deshmukh, Ge Liu

Instance-Optimal Private Density Estimation in the Wasserstein Distance

Vitaly Feldman, Audra McMillan, Satchit Sivakumar, Kunal Talwar

Constant Acceleration Flow

Dogyun Park, Sojin Lee, Sihyeon Kim, Taehoon Lee, Youngjoon Hong

Octopus: A Multi-modal LLM with Parallel Recognition and Sequential Understanding

Chuyang Zhao, Yuxin Song, Junru Chen, Kang Rong, Haocheng Feng

DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation

Hongyuan Tao, Hang Yu, Jianguo Li

Advancing Video Anomaly Detection: A Concise Review and a New Dataset

Liyun Zhu, Lei Wang, Arjun Raj, Tom Gedeon, Chen Chen

ActFusion: a Unified Diffusion Model for Action Segmentation and Anticipation

Dayoung Gong, Suha Kwak, Minsu Cho

A Theoretical Understanding of Self-Correction through In-context Alignment

Yifei Wang, Yuyang Wu, Zeming Wei, Stefanie Jegelka, Yisen Wang

FIFO-Diffusion: Generating Infinite Videos from Text without Training

Jihwan Kim, Junoh Kang, Jinyoung Choi, Bohyung Han

Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox

Xingming Long, Jie Zhang, Shiguang Shan, Xilin Chen

Enhancing Feature Diversity Boosts Channel-Adaptive Vision Transformers

Chau Pham, Bryan A. Plummer

Untrained Neural Nets for Snapshot Compressive Imaging: Theory and Algorithms

Mengyu Zhao, Xi Chen, Xin Yuan, Shirin Jalali

Doubly Hierarchical Geometric Representations for Strand-based Human Hairstyle Generation

Yunlu Chen, Francisco Vicente Carrasco, Christian Häne, Giljoo Nam, Jean-Charles Bazin

Towards Visual Text Design Transfer Across Languages

Yejin Choi, Jiwan Chung, Sumin Shim, Giyeong Oh, Youngjae Yu

TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation

Chenyang Le, Yao Qian, Dongmei Wang, Long Zhou, Shujie LIU

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models

Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei

Adversarial Schrödinger Bridge Matching

Nikita Gushchin, Daniil Selikhanovych, Sergei Kholkin, Evgeny Burnaev, Alexander Korotin

DiffusionBlend: Learning 3D Image Prior through Position-aware Diffusion Score Blending for 3D Computed Tomography Reconstruction

Bowen Song, Jason Hu, Zhaoxu Luo, Jeffrey A. Fessler, Liyue Shen

Multidimensional Fractional Programming for Normalized Cuts

Yannan Chen, Beichen Huang, Licheng Zhao, Kaiming Shen

DiffHammer: Rethinking the Robustness of Diffusion-Based Adversarial Purification

Kaibo Wang, Xiaowen Fu, Yuxuan Han, Yang Xiang

What Makes Partial-Label Learning Algorithms Effective?

Jiaqi Lv, Yangfan Liu, Shiyu Xia, Ning Xu, Miao Xu

CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM

Minkyu Jeon, Rishwanth Raghu, Miro Astore, Geoffrey Woollard, Ryan Feathers

Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox

Raymond Zhang, Richard Combes

Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation

Meihan Liu, Zhen Zhang, Jiachen Tang, Jiajun Bu, Bingsheng He

PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action

Yijia Shao, Tianshi Li, Weiyan Shi, Yanchen Liu, Diyi Yang

Revisiting motion information for RGB-Event tracking with MOT philosophy

Tianlu Zhang, Kurt Debattista, Qiang Zhang, guiguang ding, Jungong Han

EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records

Yeonsu Kwon, Jiho Kim, Gyubok Lee, Seongsu Bae, Daeun Kyung

Constrained Synthesis with Projected Diffusion Models

Jacob K. Christopher, Stephen Baek, Ferdinando Fioretto

Improved Guarantees for Fully Dynamic k-Center Clustering with Outliers in General Metric Spaces

Leyla Biabani, Annika Hennes, Denise La Gordt Dillie, Morteza Monemizadeh, Melanie Schmidt

Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.

Spandan Madan, Will Xiao, Mingran Cao, Hanspeter Pfister, Margaret Livingstone

Class Distribution Shifts in Zero-Shot Learning: Learning Robust Representations

Yuli Slavutsky, Yuval Benjamini

GaussianCut: Interactive segmentation via graph cut for 3D Gaussian Splatting

Umangi Jain, Ashkan Mirzaei, Igor Gilitschenski

Spectral Learning of Shared Dynamics Between Generalized-Linear Processes

Lucine L. Oganesian, Omid G. Sani, Maryam M. Shanechi

Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation

Shiji Zhao, Ranjie Duan, Xizhe Wang, Xingxing Wei

MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding

Xinyu Fang, Kangrui Mao, Haodong Duan, Xiangyu Zhao, Yining Li

Molecule Design by Latent Prompt Transformer

Deqian Kong, Yuhao Huang, Jianwen Xie, Edouardo Honig, Ming Xu

QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation

Gonçalo R. A. Faria, Sweta Agrawal, António Farinhas, Ricardo Rei, José G. C. de Souza

Intervention and Conditioning in Causal Bayesian Networks

Sainyam Galhotra, Joseph Y. Halpern

Compressing Large Language Models using Low Rank and Low Precision Decomposition

Rajarshi Saha, Naomi Sagan, Varun Srivastava, Andrea J. Goldsmith, Mert Pilanci

Once Read is Enough: Domain-specific Pretraining-free Language Models with Cluster-guided Sparse Experts for Long-tail Domain Knowledge

Fang Dong, Mengyi Chen, Jixian Zhou, Yubin Shi, Yixuan Chen

Decomposable Transformer Point Processes

Aristeidis Panos

Perception of Knowledge Boundary for Large Language Models through Semi-open-ended Question Answering

Zhihua Wen, Zhiliang Tian, Zexin Jian, Zhen Huang, Pei Ke

On Socially Fair Low-Rank Approximation and Column Subset Selection

Zhao Song, Ali Vakilian, David P. Woodruff, Samson Zhou

Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity

Kaja Gruntkowska, Alexander Tyurin, Peter Richtarik

Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation

Julius Vetter, Guy Moss, Cornelius Schröder, Richard Gao, Jakob H. Macke

Provable and Efficient Dataset Distillation for Kernel Ridge Regression

Yilan Chen, Wei Huang, Tsui-Wei Weng

Learning to Price Homogeneous Data

Keran Chen, Joon Suk Huh, Kirthevasan Kandasamy

Implicit Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes

Qi Ma, Danda Pani Paudel, Ender Konukoglu, Luc Van Gool

Speculative Monte-Carlo Tree Search

Scott Cheng, Mahmut Taylan Kandemir, Ding-Yong Hong

SM3-Text-to-Query: Synthetic Multi-Model Medical Text-to-Query Benchmark

Sithursan Sivasubramaniam, Cedric Osei-Akoto, Yi Zhang, Kurt Stockinger, Jonathan Fürst

A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise

Ilias Diakonikolas, Nikos Zarifis

ProtGO: Function-Guided Protein Modeling for Unified Representation Learning

Bozhen Hu, Cheng Tan, Yongjie Xu, Zhangyang Gao, Jun Xia

IDGen: Item Discrimination Induced Prompt Generation for LLM Evaluation

Fan Lin, Shuyi Xie, Yong Dai, Wenlin Yao, Tianjiao Lang

Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models

Arshia Hemmat, Adam Davies, Tom A. Lamb, Jianhao Yuan, Philip Torr

Trap-MID: Trapdoor-based Defense against Model Inversion Attacks

Zhen-Ting Liu, Shang-Tse Chen

bit2bit: 1-bit quanta video reconstruction via self-supervised photon prediction

Yehe Liu, Alexander Krull, Hector Basevi, Ales Leonardis, Michael Jenkins

Renovating Names in Open-Vocabulary Segmentation Benchmarks

Haiwen Huang, Songyou Peng, Dan Zhang, Andreas Geiger

On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games

Zhiyuan Fan, Christian Kroer, Gabriele Farina

Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains

Lei Wang, Jieming Bian, Letian Zhang, Chen Chen, Jie Xu

DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning

Xun Guo, Shan Zhang, Yongxin He, Ting Zhang, Wanquan Feng

Model-Based Transfer Learning for Contextual Reinforcement Learning

Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu

Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models

Dominik Hintersdorf, Lukas Struppek, Kristian Kersting, Adam Dziedzic, Franziska Boenisch

Transition Constrained Bayesian Optimization via Markov Decision Processes

Jose Pablo Folch, Calvin Tsay, Robert M Lee, Behrang Shafei, Weronika Ormaniec

Contextual Decision-Making with Knapsacks Beyond the Worst Case

Zhaohua Chen, Rui Ai, Mingwei Yang, Yuqi Pan, Chang Wang

Differentially Private Reinforcement Learning with Self-Play

Dan Qiao, Yu-Xiang Wang

Mixture of Demonstrations for In-Context Learning

Song Wang, Zihan Chen, Chengshuai Shi, Cong Shen, Jundong Li

An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations

Shengbo Wang, Jose Blanchet, Peter Glynn