NeurIPS 2023

3,540 papers

Test-Time Distribution Normalization for Contrastively Learned Visual-language Models

Yifei Zhou, Juntao Ren, Fengyu Li, Ramin Zabih, Ser Nam Lim

Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning

Shenzhi Wang, Qisen Yang, Jiawei Gao, Matthieu Lin, Hao Chen

A Spectral Theory of Neural Prediction and Alignment

Abdulkadir Canatar, Jenelle Feather, Albert Wakhloo, SueYeon Chung

Sharpness-Aware Minimization Leads to Low-Rank Features

Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion

Structured State Space Models for In-Context Reinforcement Learning

Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob Foerster

Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness

Ambar Pal, Jeremias Sulam, René Vidal

Explainable Brain Age Prediction using coVariance Neural Networks

Saurabh Sihag, Gonzalo Mateos, Corey McMillan, Alejandro Ribeiro

Stanford-ORB: A Real-World 3D Object Inverse Rendering Benchmark

Zhengfei Kuang, Yunzhi Zhang, Hong-Xing Yu, Samir Agarwala, Elliott / Shangzhe Wu

Structured Prediction with Stronger Consistency Guarantees

Anqi Mao, Mehryar Mohri, Yutao Zhong

CrossGNN: Confronting Noisy Multivariate Time Series Via Cross Interaction Refinement

Qihe Huang, Lei Shen, Ruixin Zhang, Shouhong Ding, Binwu Wang

Diplomat: A Dialogue Dataset for Situated PragMATic Reasoning

Hengli Li, Song-chun Zhu, Zilong Zheng

Image Captioners Are Scalable Vision Learners Too

Michael Tschannen, Manoj Kumar, Andreas Steiner, Xiaohua Zhai, Neil Houlsby

PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction

Apoorva Sharma, Sushant Veer, Asher Hancock, Heng Yang, Marco Pavone

Neural Oscillators are Universal

Samuel Lanthaler, T. Konstantin Rusch, Siddhartha Mishra

CAPP-130: A Corpus of Chinese Application Privacy Policy Summarization and Interpretation

pengyun zhu, Long Wen, Jinfei Liu, Feng Xue, Jian Lou

Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness

Evgenii Chzhen, Christophe Giraud, Zhen Li, Gilles Stoltz

Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning

Yangru Huang, Peixi Peng, Yifan Zhao, Haoran Xu, Mengyue Geng

CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion

Yangruibo Ding, Zijian Wang, Wasi Ahmad, Hantian Ding, Ming Tan

Fine-grained Expressivity of Graph Neural Networks

Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris

Causal Discovery in Semi-Stationary Time Series

Shanyun Gao, Raghavendra Addanki, Tong Yu, Ryan Rossi, Murat Kocaoglu

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu

Self-Refine: Iterative Refinement with Self-Feedback

Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao

Pairwise Causality Guided Transformers for Event Sequences

Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh

TaskMet: Task-driven Metric Learning for Model Learning

Dishank Bansal, Ricky T. Q. Chen, Mustafa Mukadam, Brandon Amos

LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition

Haoxuan Qu, Xiaofei Hui, Yujun Cai, Jun Liu

Estimating Causal Effects Identifiable from a Combination of Observations and Experiments

Yonghan Jung, Ivan Diaz, Jin Tian, Elias Bareinboim

Cola: A Benchmark for Compositional Text-to-image Retrieval

Arijit Ray, Filip Radenovic, Abhimanyu Dubey, Bryan Plummer, Ranjay Krishna

Unified 3D Segmenter As Prototypical Classifiers

Zheyun Qin, Cheng Han, Qifan Wang, Xiushan Nie, Yilong Yin

Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations

Minshuo Chen, Yu Bai, H. Vincent Poor, Mengdi Wang

A Reduction-based Framework for Sequential Decision Making with Delayed Feedback

Yunchang Yang, Han Zhong, Tianhao Wu, Bin Liu, Liwei Wang

Learning to Tokenize for Generative Retrieval

Weiwei Sun, Lingyong Yan, Zheng Chen, Shuaiqiang Wang, Haichao Zhu

Synthetic Experience Replay

Cong Lu, Philip Ball, Yee Whye Teh, Jack Parker-Holder

ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion

Yingjun Du, Zehao Xiao, Shengcai Liao, Cees Snoek

Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models

Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl

Brain Dissection: fMRI-trained Networks Reveal Spatial Selectivity in the Processing of Natural Images

Gabriel Sarch, Michael Tarr, Katerina Fragkiadaki, Leila Wehbe

TabMT: Generating tabular data with masked transformers

Manbir Gulati, Paul Roysdon

EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understanding

Karttikeya Mangalam, Raiymbek Akshulakov, Jitendra Malik

Variational Gaussian Processes with Decoupled Conditionals

Xinran Zhu, Kaiwen Wu, Natalie Maus, Jacob Gardner, David Bindel

Hierarchical VAEs provide a normative account of motion processing in the primate brain

Hadi Vafaii, Jacob Yates, Daniel Butts

DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions

Haochen Wang, Junsong Fan, Yuxi Wang, Kaiyou Song, Tong Wang

On the Minimax Regret for Online Learning with Feedback Graphs

Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-bianchi

Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning

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

Principled Weight Initialisation for Input-Convex Neural Networks

Pieter-Jan Hoedt, Günter Klambauer

Active Observing in Continuous-time Control

Samuel Holt, Alihan Hüyük, Mihaela van der Schaar

PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds

Hao Yang, Haiyang Wang, Di Dai, Liwei Wang

GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising

Hyeonsu Kim, Jeheon Woo, SEONGHWAN KIM, Seokhyun Moon, Jun Hyeong Kim

Learning Time-Invariant Representations for Individual Neurons from Population Dynamics

Lu Mi, Trung Le, Tianxing He, Eli Shlizerman, Uygar Sümbül

Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows

Lauren Conger, Franca Hoffmann, Eric Mazumdar, Lillian Ratliff

Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond

Omar Chehab, Aapo Hyvärinen, Andrej Risteski

Exploring Geometry of Blind Spots in Vision models

Sriram Balasubramanian, Gaurang Sriramanan, Vinu Sankar Sadasivan, Soheil Feizi

Transformer-based Planning for Symbolic Regression

Parshin Shojaee, Kazem Meidani, Amir Barati Farimani, Chandan Reddy

CLIP4HOI: Towards Adapting CLIP for Practical Zero-Shot HOI Detection

Yunyao Mao, Jiajun Deng, Wengang Zhou, Li Li, Yao Fang

ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings

Shibo Hao, Tianyang Liu, Zhen Wang, Zhiting Hu

ExPT: Synthetic Pretraining for Few-Shot Experimental Design

Tung Nguyen, Sudhanshu Agrawal, Aditya Grover

PDP: Parameter-free Differentiable Pruning is All You Need

Minsik Cho, Saurabh Adya, Devang Naik

AGD: an Auto-switchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix

Yun Yue, Zhiling Ye, Jiadi Jiang, Yongchao Liu, Ke ZHANG

Multimodal Clinical Benchmark for Emergency Care (MC-BEC): A Comprehensive Benchmark for Evaluating Foundation Models in Emergency Medicine

Emma Chen, Aman Kansal, Julie Chen, Boyang Tom Jin, Julia Reisler

Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers

Zixuan Jiang, Jiaqi Gu, Hanqing Zhu, David Pan

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk

Pgx: Hardware-Accelerated Parallel Game Simulators for Reinforcement Learning

Sotetsu Koyamada, Shinri Okano, Soichiro Nishimori, Yu Murata, Keigo Habara

STREAMER: Streaming Representation Learning and Event Segmentation in a Hierarchical Manner

Ramy Mounir, Sujal Vijayaraghavan, Sudeep Sarkar

VaRT: Variational Regression Trees

Sebastian Salazar

Linear Time Algorithms for k-means with Multi-Swap Local Search

Junyu Huang, Qilong Feng, Ziyun Huang, Jinhui Xu, Jianxin Wang

Transformers learn to implement preconditioned gradient descent for in-context learning

Kwangjun Ahn, Xiang Cheng, Hadi Daneshmand, Suvrit Sra

Learning Invariant Representations of Graph Neural Networks via Cluster Generalization

Donglin Xia, Xiao Wang, Nian Liu, Chuan Shi

A normative theory of social conflict

Sergey Shuvaev, Evgeny Amelchenko, Dmitry Smagin, Natalia Kudryavtseva, Grigori Enikolopov

SatLM: Satisfiability-Aided Language Models Using Declarative Prompting

Xi Ye, Qiaochu Chen, Isil Dillig, Greg Durrett

A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence

Junyi Zhang, Charles Herrmann, Junhwa Hur, Luisa Polania Cabrera, Varun Jampani

Graph Contrastive Learning with Stable and Scalable Spectral Encoding

Deyu Bo, Yuan Fang, Yang Liu, Chuan Shi

Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions

Tongxin Li, Yiheng Lin, Shaolei Ren, Adam Wierman

Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies

Oscar Li, James Harrison, Jascha Sohl-dickstein, Virginia Smith, Luke Metz

Disentanglement via Latent Quantization

Kyle Hsu, William Dorrell, James Whittington, Jiajun Wu, Chelsea Finn

Learning Linear Causal Representations from Interventions under General Nonlinear Mixing

Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf

Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning

Stephen Mcaleer, Gabriele Farina, Gaoyue Zhou, Mingzhi Wang, Yaodong Yang

Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection

Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Ozgur

Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics

Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang

Learning to Group Auxiliary Datasets for Molecule

Tinglin Huang, Ziniu Hu, Rex Ying

Energy Discrepancies: A Score-Independent Loss for Energy-Based Models

Tobias Schröder, Zijing Ou, Jen Lim, Yingzhen Li, Sebastian Vollmer

Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs

Yunsheng Bai, Atefeh Sohrabizadeh, Zongyue Qin, Ziniu Hu, Yizhou Sun

DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Salva Rühling Cachay, Bo Zhao, Hailey Joren, Rose Yu

Unified Segment-to-Segment Framework for Simultaneous Sequence Generation

Shaolei Zhang, Yang Feng

A State Representation for Diminishing Rewards

Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana Borsa, Maneesh Sahani

Regression with Cost-based Rejection

Xin Cheng, Yuzhou Cao, Haobo Wang, Hongxin Wei, Bo An

ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentation

Zhitong Gao, Shipeng Yan, Xuming He

Tame a Wild Camera: In-the-Wild Monocular Camera Calibration

Shengjie Zhu, Abhinav Kumar, Masa Hu, Xiaoming Liu

Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures

Hamish Flynn, David Reeb, Melih Kandemir, Jan R. Peters, Jan R Peters

Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes

Walter Gerych, Kevin Hickey, Luke Buquicchio, Kavin Chandrasekaran, Abdulaziz Alajaji

On the Gini-impurity Preservation For Privacy Random Forests

XinRan Xie, Man-Jie Yuan, Xuetong Bai, Wei Gao, Zhi-Hua Zhou

PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning

Florian Bordes, Shashank Shekhar, Mark Ibrahim, Diane Bouchacourt, Pascal Vincent

Adaptive Contextual Perception: How To Generalize To New Backgrounds and Ambiguous Objects

Zhuofan Ying, Peter Hase, Mohit Bansal

PTADisc: A Cross-Course Dataset Supporting Personalized Learning in Cold-Start Scenarios

Liya Hu, Zhiang Dong, Jingyuan Chen, Guifeng Wang, Zhihua Wang

Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition

Wei He, Kai Han, Ying Nie, Chengcheng Wang, Yunhe Wang

A Unified, Scalable Framework for Neural Population Decoding

Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu

REx: Data-Free Residual Quantization Error Expansion

Edouard YVINEC, Arnaud Dapogny, Matthieu Cord, Kevin Bailly

Optimizing over trained GNNs via symmetry breaking

Shiqiang Zhang, Juan Campos, Christian Feldmann, David Walz, Frederik Sandfort

KuaiSim: A Comprehensive Simulator for Recommender Systems

Kesen Zhao, Shuchang Liu, Qingpeng Cai, Xiangyu Zhao, Ziru Liu

OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding

Minghua Liu, Ruoxi Shi, Kaiming Kuang, Yinhao Zhu, Xuanlin Li

A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective

Chenhang Cui, Yazhou Ren, Jingyu Pu, Jiawei Li, Xiaorong Pu

Fair, Polylog-Approximate Low-Cost Hierarchical Clustering

Marina Knittel, Max Springer, John Dickerson, MohammadTaghi Hajiaghayi

First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities

Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander Gasnikov, Alexey Naumov