NeurIPS 2023

3,540 papers

NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning

Yun Yi, Haokui Zhang, Rong Xiao, Nannan Wang, Xiaoyu Wang

MiliPoint: A Point Cloud Dataset for mmWave Radar

Han Cui, Shu Zhong, Jiacheng Wu, Zichao Shen, Naim Dahnoun

Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning

Arnaud Robert, Ciara Pike-Burke, Aldo A Faisal

A Recurrent Neural Circuit Mechanism of Temporal-scaling Equivariant Representation

Junfeng Zuo, Xiao Liu, Ying Nian Wu, Si Wu, Wenhao Zhang

Distributionally Robust Ensemble of Lottery Tickets Towards Calibrated Sparse Network Training

Hitesh Sapkota, Dingrong Wang, Zhiqiang Tao, Qi Yu

Guiding Large Language Models via Directional Stimulus Prompting

Zekun Li, Baolin Peng, Pengcheng He, Michel Galley, Jianfeng Gao

Regularity as Intrinsic Reward for Free Play

Cansu Sancaktar, Justus Piater, Georg Martius

RECKONING: Reasoning through Dynamic Knowledge Encoding

Zeming Chen, Gail Weiss, Eric Mitchell, Asli Celikyilmaz, Antoine Bosselut

BERT Lost Patience Won't Be Robust to Adversarial Slowdown

Zachary Coalson, Gabriel Ritter, Rakesh Bobba, Sanghyun Hong

Federated Linear Bandits with Finite Adversarial Actions

Li Fan, Ruida Zhou, Chao Tian, Cong Shen

Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off

Zichen (Vincent) Zhang, Johannes Kirschner, Junxi Zhang, Francesco Zanini, Alex Ayoub

Faster Margin Maximization Rates for Generic Optimization Methods

Guanghui Wang, Zihao Hu, Vidya Muthukumar, Jacob D. Abernethy

StateMask: Explaining Deep Reinforcement Learning through State Mask

Zelei Cheng, Xian Wu, Jiahao Yu, Wenhai Sun, Wenbo Guo

UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction

Yansong Ning, Hao Liu, Hao Wang, Zhenyu Zeng, Hui Xiong

EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning

Mohammad Mahdi Rahimi, Hasnain Irshad Bhatti, Younghyun Park, Humaira Kousar, Jaekyun Moon

Pruning vs Quantization: Which is Better?

Andrey Kuzmin, Markus Nagel, Mart van Baalen, Arash Behboodi, Tijmen Blankevoort

Stability Guarantees for Feature Attributions with Multiplicative Smoothing

Anton Xue, Rajeev Alur, Eric Wong

FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation

Yuanxin Liu, Lei Li, Shuhuai Ren, Rundong Gao, Shicheng Li

ReTR: Modeling Rendering Via Transformer for Generalizable Neural Surface Reconstruction

Yixun Liang, Hao He, Yingcong Chen

Metropolis Sampling for Constrained Diffusion Models

Nic Fishman, Leo Klarner, Emile Mathieu, Michael Hutchinson, Valentin De Bortoli

PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning

Hojoon Lee, Hanseul Cho, HYUNSEUNG KIM, DAEHOON GWAK, Joonkee Kim

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning

Mitsuhiko Nakamoto, Simon Zhai, Anikait Singh, Max Sobol Mark, Yi Ma

Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction

Ruoyu Li, Qing Li, Yu Zhang, Dan Zhao, Yong Jiang

Diffusion Schrödinger Bridge Matching

Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet

EV-Eye: Rethinking High-frequency Eye Tracking through the Lenses of Event Cameras

Guangrong Zhao, Yurun Yang, Jingwei Liu, Ning Chen, Yiran Shen

The Target-Charging Technique for Privacy Analysis across Interactive Computations

Edith Cohen, Xin Lyu

Recurrent Hypernetworks are Surprisingly Strong in Meta-RL

Jacob Beck, Risto Vuorio, Zheng Xiong, Shimon Whiteson

Survival Instinct in Offline Reinforcement Learning

Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng

One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning

Shaochen (Henry) Zhong, Zaichuan You, Jiamu Zhang, Sebastian Zhao, Zachary LeClaire

Fed-FA: Theoretically Modeling Client Data Divergence for Federated Language Backdoor Defense

Zhiyuan Zhang, Deli Chen, Hao Zhou, Fandong Meng, Jie Zhou

Reinforcement Learning with Simple Sequence Priors

Tankred Saanum, Noemi Elteto, Peter Dayan, Marcel Binz, Eric Schulz

Equivariant Neural Operator Learning with Graphon Convolution

Chaoran Cheng, Jian Peng

Approximation-Generalization Trade-offs under (Approximate) Group Equivariance

Mircea Petrache, Shubhendu Trivedi

Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples

Shashanka Venkataramanan, Ewa Kijak, laurent amsaleg, Yannis Avrithis

Solving Inverse Physics Problems with Score Matching

Benjamin Holzschuh, Simona Vegetti, Nils Thuerey

LICO: Explainable Models with Language-Image COnsistency

Yiming Lei, Zilong Li, Yangyang Li, Junping Zhang, Hongming Shan

Residual Q-Learning: Offline and Online Policy Customization without Value

Chenran Li, Chen Tang, Haruki Nishimura, Jean Mercat, Masayoshi Tomizuka

On the Exploitability of Instruction Tuning

Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao

Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning

Alex Tamkin, Margalit Glasgow, Xiluo He, Noah Goodman

DAW: Exploring the Better Weighting Function for Semi-supervised Semantic Segmentation

Rui Sun, Huayu Mai, Tianzhu Zhang, Feng Wu

Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration

Theo Adrai, Guy Ohayon, Michael Elad, Tomer Michaeli

Hierarchical Multi-Agent Skill Discovery

Mingyu Yang, Yaodong Yang, Zhenbo Lu, Wengang Zhou, Houqiang Li

Improving the Knowledge Gradient Algorithm

Le Yang, Siyang Gao, Chin Pang Ho

The Bayesian Stability Zoo

Shay Moran, Hilla Schefler, Jonathan Shafer

Unleashing the Full Potential of Product Quantization for Large-Scale Image Retrieval

Yu Liang, Shiliang Zhang, Li Ken Li, Xiaoyu Wang

A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization

Yuanyuan Liu, Fanhua Shang, Weixin An, Junhao Liu, Hongying Liu

Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer

Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na

Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents

Nika Haghtalab, Chara Podimata, Kunhe Yang

First- and Second-Order Bounds for Adversarial Linear Contextual Bandits

Julia Olkhovskaya, Jack Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei

For SALE: State-Action Representation Learning for Deep Reinforcement Learning

Scott Fujimoto, Wei-Di Chang, Edward Smith, Shixiang (Shane) Gu, Doina Precup

Regret Matching+: (In)Stability and Fast Convergence in Games

Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo

Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities

Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius

VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks

Wenhai Wang, Zhe Chen, Xiaokang Chen, Jiannan Wu, Xizhou Zhu

Are aligned neural networks adversarially aligned?

Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao

ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fields

Jiahua Dong, Yu-Xiong Wang

SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning

JunHoo Lee, Jayeon Yoo, Nojun Kwak

Chatting Makes Perfect: Chat-based Image Retrieval

Matan Levy, Rami Ben-Ari, Nir Darshan, Dani Lischinski

Offline Reinforcement Learning with Differential Privacy

Dan Qiao, Yu-Xiang Wang

Cognitive Model Discovery via Disentangled RNNs

Kevin Miller, Maria Eckstein, Matt Botvinick, Zeb Kurth-Nelson

The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions

Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp

Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources

Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia

Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization

Yankun Huang, Qihang Lin

Provable benefits of score matching

Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari, Holden Lee, Ankur Moitra

Validated Image Caption Rating Dataset

Lothar D Narins, Andrew Scott, Aakash Gautam, Anagha Kulkarni, Mar Castanon

Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent

Tianle Liu, Promit Ghosal, Krishnakumar Balasubramanian, Natesh Pillai

A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning

Hangfan Zhang, Jinyuan Jia, Jinghui Chen, Lu Lin, Dinghao Wu

S-CLIP: Semi-supervised Vision-Language Learning using Few Specialist Captions

Sangwoo Mo, Minkyu Kim, Kyungmin Lee, Jinwoo Shin

GRAND-SLAMIN’ Interpretable Additive Modeling with Structural Constraints

Shibal Ibrahim, Gabriel Afriat, Kayhan Behdin, Rahul Mazumder

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond

Thanh Nguyen-Tang, Raman Arora

A Unified Approach for Maximizing Continuous DR-submodular Functions

Mohammad Pedramfar, Christopher Quinn, Vaneet Aggarwal

On the Size and Approximation Error of Distilled Datasets

Alaa Maalouf, Murad Tukan, Noel Loo, Ramin Hasani, Mathias Lechner

InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding

Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang

On the Constrained Time-Series Generation Problem

Andrea Coletta, Sriram Gopalakrishnan, Daniel Borrajo, Svitlana Vyetrenko

MeCo: Zero-Shot NAS with One Data and Single Forward Pass via Minimum Eigenvalue of Correlation

Tangyu Jiang, Haodi Wang, Rongfang Bie

Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction

Yangqing Fu, Ming Sun, Buqing Nie, Yue Gao

Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning

Cristina Menghini, Andrew Delworth, Stephen Bach

Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions

Ruihai Wu, Kai Cheng, Yan Zhao, Chuanruo Ning, Guanqi Zhan

Do Not Marginalize Mechanisms, Rather Consolidate!

Moritz Willig, Matej Zečević, Devendra Dhami, Kristian Kersting

An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient

Yudong Luo, Guiliang Liu, Pascal Poupart, Yangchen Pan

RETVec: Resilient and Efficient Text Vectorizer

Elie Bursztein, Marina Zhang, Owen Vallis, XINYU JIA, Alexey Kurakin

Dream the Impossible: Outlier Imagination with Diffusion Models

Xuefeng Du, Yiyou Sun, Xiaojin Zhu, Yixuan Li

Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity

Zhanpeng Zhou, Yongyi Yang, Xiaojiang Yang, Junchi Yan, Wei Hu

Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices

Guillaume Wang, Lénaïc Chizat

Scaling MLPs: A Tale of Inductive Bias

Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann

Soft-Unification in Deep Probabilistic Logic

Jaron Maene, Luc De Raedt

Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation

Jiachen Liang, Ruibing Hou, Hong Chang, Bingpeng MA, Shiguang Shan

ResMem: Learn what you can and memorize the rest

Zitong Yang, MICHAL LUKASIK, Vaishnavh Nagarajan, Zonglin Li, Ankit Rawat

Aiming towards the minimizers: fast convergence of SGD for overparametrized problems

Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yian Ma

Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation

Zhangsihao Yang, Mengwei Ren, Kaize Ding, Guido Gerig, Yalin Wang

Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning

Marina Munkhoeva, Ivan Oseledets

Dynamic Regret of Adversarial Linear Mixture MDPs

Peng Zhao, Zhi-Hua Zhou, Longfei Li, Long-Fei Li

Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships

ABHRA CHAUDHURI, Massimiliano Mancini, Zeynep Akata, Anjan Dutta

Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model

Luning Sun, Xu Han, Han Gao, Jian-Xun Wang, Liping Liu

Reward-Directed Conditional Diffusion: Provable Distribution Estimation and Reward Improvement

Hui Yuan, Kaixuan Huang, Chengzhuo Ni, Minshuo Chen, Mengdi Wang

Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach

Phillip Pope, David Jacobs

Geometric Analysis of Matrix Sensing over Graphs

Haixiang Zhang, Ying Chen, Javad Lavaei

Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings

Yi Ren, Samuel Lavoie, Michael Galkin, Danica J. Sutherland, Aaron C. Courville

The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning

Artyom Gadetsky, Maria Brbic

Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards

Hao Qin, Kwang-Sung Jun, Chicheng Zhang

Learning Nonparametric Latent Causal Graphs with Unknown Interventions

Yibo Jiang, Bryon Aragam