NeurIPS 2023

3,540 papers

Optimal Algorithms for the Inhomogeneous Spiked Wigner Model

Aleksandr Pak, Justin Ko, Florent Krzakala

Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models

Geon Yeong Park, Jeongsol Kim, Beomsu Kim, Sang Wan Lee, Jong Chul Ye

Adversarially Robust Distributed Count Tracking via Partial Differential Privacy

Zhongzheng Xiong, Xiaoyi Zhu, zengfeng Huang

When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Duncan McElfresh, Sujay Khandagale, Jonathan Valverde, Vishak Prasad C, Ganesh Ramakrishnan

AdANNS: A Framework for Adaptive Semantic Search

Aniket Rege, Aditya Kusupati, Sharan Ranjit S, Alan Fan, Qingqing Cao

LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning

Atsuyuki Miyai, Qing Yu, Go Irie, Kiyoharu Aizawa

Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy

Amit Daniely, Nati Srebro, Gal Vardi

Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems

Fiona Lippert, Bart Kranstauber, Emiel van Loon, Patrick Forré

Predicting a Protein's Stability under a Million Mutations

Jeffrey Ouyang-Zhang, Daniel Diaz, Adam Klivans, Philipp Kraehenbuehl

Deep Insights into Noisy Pseudo Labeling on Graph Data

Botao WANG, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong

Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent

Xixi Jia, Hailin Wang, Jiangjun Peng, Xiangchu Feng, Deyu Meng

Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release

Yufan Li, Jialiang Mao, Iavor Bojinov

Latent SDEs on Homogeneous Spaces

Sebastian Zeng, Florian Graf, Roland Kwitt

Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models

Sivan Doveh, Assaf Arbelle, Sivan Harary, Roei Herzig, Donghyun Kim

GLOBER: Coherent Non-autoregressive Video Generation via GLOBal Guided Video DecodER

Mingzhen Sun, Weining Wang, Zihan Qin, Jiahui Sun, Sihan Chen

Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning

Fuqi Jia, Yuhang Dong, Minghao Liu, Pei Huang, Feifei Ma

Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation

Jia-Xing Zhong, Ta-Ying Cheng, Yuhang He, Kai Lu, Kaichen Zhou

NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations

Varun Jampani, Kevis-kokitsi Maninis, Andreas Engelhardt, Arjun Karpur, Karen Truong

How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model

Michael Hanna, Ollie Liu, Alexandre Variengien

Is RLHF More Difficult than Standard RL? A Theoretical Perspective

Yuanhao Wang, Qinghua Liu, Chi Jin

On the Planning Abilities of Large Language Models - A Critical Investigation

Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan, Subbarao Kambhampati

Bayesian Risk-Averse Q-Learning with Streaming Observations

Yuhao Wang, Enlu Zhou

DiffComplete: Diffusion-based Generative 3D Shape Completion

Ruihang Chu, Enze Xie, Shentong Mo, Zhenguo Li, Matthias Niessner

SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data

Mélisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi

Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions

Vladimir Feinberg, Xinyi Chen, Y. Jennifer Sun, Rohan Anil, Elad Hazan

Towards Label-free Scene Understanding by Vision Foundation Models

Runnan Chen, Youquan Liu, Lingdong Kong, Nenglun Chen, Xinge ZHU

Compact Neural Volumetric Video Representations with Dynamic Codebooks

Haoyu Guo, Sida Peng, Yunzhi Yan, Linzhan Mou, Yujun Shen

A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games

Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman Ozdaglar, Adam Wierman

Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection

Xilie Xu, Jingfeng ZHANG, Feng Liu, Masashi Sugiyama, Mohan S Kankanhalli

Query-based Temporal Fusion with Explicit Motion for 3D Object Detection

Jinghua Hou, Zhe Liu, dingkang liang, Zhikang Zou, Xiaoqing Ye

Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models

Andrew Luo, Maggie Henderson, Leila Wehbe, Michael Tarr

EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset

Hao Tang, Kevin J Liang, Kristen Grauman, Matt Feiszli, Weiyao Wang

FIND: A Function Description Benchmark for Evaluating Interpretability Methods

Sarah Schwettmann, Tamar Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li

How Re-sampling Helps for Long-Tail Learning?

Jiang-Xin Shi, Tong Wei, Yuke Xiang, Yu-feng Li

Evaluating Neuron Interpretation Methods of NLP Models

Yimin Fan, Fahim Dalvi, Nadir Durrani, Hassan Sajjad

Universality and Limitations of Prompt Tuning

Yihan Wang, Jatin Chauhan, Wei Wang, Cho-jui Hsieh

Learning Causal Models under Independent Changes

Sarah Mameche, David Kaltenpoth, Jilles Vreeken

Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts

Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova

On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms

Lam Nguyen, Trang H. Tran

Entropic Neural Optimal Transport via Diffusion Processes

Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry P Vetrov, Evgeny Burnaev

CEIL: Generalized Contextual Imitation Learning

Jinxin Liu, LI He, Yachen Kang, Zifeng Zhuang, Donglin Wang

On Convergence of Polynomial Approximations to the Gaussian Mixture Entropy

Caleb Dahlke, Jason Pacheco

AirDelhi: Fine-Grained Spatio-Temporal Particulate Matter Dataset From Delhi For ML based Modeling

Sachin Chauhan, Zeel Bharatkumar Patel, Sayan Ranu, Rijurekha Sen, Nipun Batra

SANFlow: Semantic-Aware Normalizing Flow for Anomaly Detection

Daehyun Kim, Sungyong Baik, Taehyun Kim, Tae Hyun Kim

Activity Grammars for Temporal Action Segmentation

Dayoung Gong, Joonseok Lee, Deunsol Jung, Suha Kwak, Minsu Cho

Language Models Meet World Models: Embodied Experiences Enhance Language Models

Jiannan Xiang, Tianhua Tao, Yi Gu, Tianmin Shu, Zirui Wang

What Can We Learn from Unlearnable Datasets?

Pedro Sandoval-Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting

Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang

Langevin Quasi-Monte Carlo

Sifan Liu

Scalable 3D Captioning with Pretrained Models

Tiange Luo, Chris Rockwell, Honglak Lee, Justin Johnson

Towards Stable Backdoor Purification through Feature Shift Tuning

Rui Min, Zeyu Qin, Li Shen, Minhao Cheng

Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels

Zifu Wang, Xuefei Ning, Matthew Blaschko

Knowledge Distillation Performs Partial Variance Reduction

Mher Safaryan, Alexandra Peste, Dan Alistarh

Episodic Multi-Task Learning with Heterogeneous Neural Processes

Jiayi Shen, Xiantong Zhen, Qi Wang, Marcel Worring

Streaming Algorithms and Lower Bounds for Estimating Correlation Clustering Cost

Sepehr Assadi, Vihan Shah, Chen Wang

DAC-DETR: Divide the Attention Layers and Conquer

Zhengdong Hu, Yifan Sun, Jingdong Wang, Yi Yang

MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting

Felix Biggs, Antonin Schrab, Arthur Gretton

Adversarial Training from Mean Field Perspective

Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki

Quantizable Transformers: Removing Outliers by Helping Attention Heads Do Nothing

Yelysei Bondarenko, Markus Nagel, Tijmen Blankevoort

DIFFER:Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning

Xunhan Hu, Jian Zhao, Wengang Zhou, Ruili Feng, Houqiang Li

Advice Querying under Budget Constraint for Online Algorithms

Ziyad Benomar, Vianney Perchet

ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling

Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover

TRIAGE: Characterizing and auditing training data for improved regression

Nabeel Seedat, Jonathan Crabbe, Zhaozhi Qian, Mihaela van der Schaar

Language-based Action Concept Spaces Improve Video Self-Supervised Learning

Kanchana Ranasinghe, Michael S. Ryoo, Michael S Ryoo

Static and Sequential Malicious Attacks in the Context of Selective Forgetting

Chenxu Zhao, Wei Qian, Rex Ying, Mengdi Huai

Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Miles Turpin, Julian Michael, Ethan Perez, Samuel Bowman

SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations

Youngsoo Jang, Geon-hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim

The noise level in linear regression with dependent data

Ingvar Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni

Anchor Data Augmentation

Nora Schneider, Shirin Goshtasbpour, Fernando Pérez-Cruz

(Amplified) Banded Matrix Factorization: A unified approach to private training

Christopher A. Choquette-Choo, Arun Ganesh, Ryan McKenna, H. Brendan McMahan, John Rush

Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards

Mengfan Xu, Diego Klabjan

Trial matching: capturing variability with data-constrained spiking neural networks

Christos Sourmpis, Carl Petersen, Wulfram Gerstner, Guillaume Bellec

How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot

FedNAR: Federated Optimization with Normalized Annealing Regularization

Junbo Li, Ang Li, Chong Tian, Qirong Ho, Eric P. Xing

Probabilistic Invariant Learning with Randomized Linear Classifiers

Leonardo Cotta, Gal Yehuda, Assaf Schuster, Chris J Maddison

Replicability in Reinforcement Learning

Amin Karbasi, Grigoris Velegkas, Lin Yang, Felix Zhou

Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction

Zeshuai Deng, Zhuokun Chen, Shuaicheng Niu, Thomas Li, Bohan Zhuang

Unconstrained Dynamic Regret via Sparse Coding

Zhiyu Zhang, Ashok Cutkosky, Yannis Paschalidis

Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data

Praveen Venkatesh, Corbett Bennett, Sam Gale, Tamina Ramirez, Greggory Heller

Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu

Expressivity-Preserving GNN Simulation

Fabian Jogl, Maximilian Thiessen, Thomas Gärtner

Augmenting Language Models with Long-Term Memory

Weizhi Wang, Li Dong, Hao Cheng, Xiaodong Liu, Xifeng Yan

WildfireSpreadTS: A dataset of multi-modal time series for wildfire spread prediction

Sebastian Gerard, Yu Zhao, Josephine Sullivan

Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy

Dongmin Park, Seola Choi, Doyoung Kim, Hwanjun Song, Jae-Gil Lee

Where Did I Come From? Origin Attribution of AI-Generated Images

Zhenting Wang, Chen Chen, Yi Zeng, Lingjuan Lyu, Shiqing Ma

AutoGO: Automated Computation Graph Optimization for Neural Network Evolution

Mohammad Salameh, Keith Mills, Negar Hassanpour, Fred Han, Shuting Zhang

RaLEs: a Benchmark for Radiology Language Evaluations

Juanma Zambrano Chaves, Nandita Bhaskhar, Maayane Attias, Jean-Benoit Delbrouck, Daniel Rubin

DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets

Lazar Atanackovic, Alexander Tong, Bo Wang, Leo J Lee, Yoshua Bengio

H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation

Yanjie Ze, Yuyao Liu, Ruizhe Shi, Jiaxin Qin, Zhecheng Yuan

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

Samuel Dooley, Rhea Sukthanker, John Dickerson, Colin White, Frank Hutter

Object Reprojection Error (ORE): Camera pose benchmarks from lightweight tracking annotations

Xingyu Chen, Weiyao Wang, Hao Tang, Matt Feiszli

Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks

Zihao Wang, Lei Wu

Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods

Junchi Yang, Xiang Li, Ilyas Fatkhullin, Niao He

Implicit Bias of Gradient Descent for Logistic Regression at the Edge of Stability

Jingfeng Wu, Vladimir braverman, Jason Lee

P-Flow: A Fast and Data-Efficient Zero-Shot TTS through Speech Prompting

Sungwon Kim, Kevin Shih, rohan badlani, Joao Felipe Santos, Evelina Bakhturina

Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation

Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao

Characterization and Learning of Causal Graphs with Small Conditioning Sets

Murat Kocaoglu

Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation

Haoran Chen, Xintong Han, Zuxuan Wu, Yu-Gang Jiang

Breaking the Communication-Privacy-Accuracy Tradeoff with f-Differential Privacy

Richeng Jin, Zhonggen Su, caijun zhong, Zhaoyang Zhang, Tony Quek

Many-body Approximation for Non-negative Tensors

Kazu Ghalamkari, Mahito Sugiyama, Yoshinobu Kawahara