NeurIPS 2023

3,540 papers

American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers

Melissa Dell, Jacob Carlson, Tom Bryan, Emily Silcock, Abhishek Arora

CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography

Jiwen Yu, Xuanyu Zhang, Youmin Xu, Jian Zhang

Convolutional State Space Models for Long-Range Spatiotemporal Modeling

Jimmy Smith, Shalini De Mello, Jan Kautz, Scott Linderman, Wonmin Byeon

Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time

Xiang Ji, Gen Li

Optimal testing using combined test statistics across independent studies

Lasse Vuursteen, Botond Szabo, Aad van der Vaart, Harry van Zanten

Fair Graph Distillation

Qizhang Feng, Zhimeng (Stephen) Jiang, Ruiquan Li, Yicheng Wang, Na Zou

Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning

Van Cuong Pham, Cuong Nguyen, Trung Le, Dinh Phung, Gustavo Carneiro

Active representation learning for general task space with applications in robotics

Yifang Chen, Yingbing Huang, Simon S Du, Kevin G. Jamieson, Guanya Shi

Coupled Reconstruction of Cortical Surfaces by Diffeomorphic Mesh Deformation

Hao Zheng, Hongming Li, Yong Fan

Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation

Dogyoon Song, Kyunghee Han

Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization

Yan Sun, Li Shen, Dacheng Tao

Rehearsal Learning for Avoiding Undesired Future

Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou

Red Teaming Deep Neural Networks with Feature Synthesis Tools

Stephen Casper, Tong Bu, Yuxiao Li, Jiawei Li, Kevin Zhang

Auslan-Daily: Australian Sign Language Translation for Daily Communication and News

Xin Shen, Shaozu Yuan, Hongwei Sheng, Heming Du, Xin Yu

SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization

Songtao Lu

Align Your Prompts: Test-Time Prompting with Distribution Alignment for Zero-Shot Generalization

Jameel Abdul Samadh, Mohammad Hanan Gani, Noor Hussein, Muhammad Uzair Khattak, Muhammad Muzammal Naseer

Data Quality in Imitation Learning

Suneel Belkhale, Yuchen Cui, Dorsa Sadigh

Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity

Joel Ye, Jennifer Collinger, Leila Wehbe, Robert Gaunt

Max-Sliced Mutual Information

Dor Tsur, Ziv Goldfeld, Kristjan Greenewald

Conformal Prediction for Uncertainty-Aware Planning with Diffusion Dynamics Model

Jiankai Sun, Yiqi Jiang, Jianing Qiu, Parth Nobel, Mykel J Kochenderfer

Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models

Siyan Zhao, Aditya Grover

Scaling Riemannian Diffusion Models

Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon

Provably Bounding Neural Network Preimages

Suhas Kotha, Christopher Brix, J. Zico Kolter, Krishnamurthy Dvijotham, Huan Zhang

On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences

Alireza F. Pour, Hassan Ashtiani

Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals

Tam Nguyen, Tan Nguyen, Richard Baraniuk

Harnessing the power of choices in decision tree learning

Guy Blanc, Jane Lange, Chirag Pabbaraju, Colin Sullivan, Li-Yang Tan

Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation

Richard Gao, Michael Deistler, Jakob H. Macke, Jakob H Macke

PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model

Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua Susskind

Depth-discriminative Metric Learning for Monocular 3D Object Detection

Wonhyeok Choi, Mingyu Shin, Sunghoon Im

LogSpecT: Feasible Graph Learning Model from Stationary Signals with Recovery Guarantees

Shangyuan LIU, Linglingzhi Zhu, Anthony Man-Cho So

Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions

Duligur Ibeling, Thomas Icard

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning

Mhairi Dunion, Trevor McInroe, Kevin Luck, Josiah Hanna, Stefano Albrecht

Jailbroken: How Does LLM Safety Training Fail?

Alexander Wei, Nika Haghtalab, Jacob Steinhardt

New Bounds for Hyperparameter Tuning of Regression Problems Across Instances

Maria-Florina F Balcan, Anh Nguyen, Dravyansh Sharma

Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask?

Hoang Pham, The Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le

Context Shift Reduction for Offline Meta-Reinforcement Learning

Yunkai Gao, Rui Zhang, Jiaming Guo, Fan Wu, Qi Yi

A Riemannian Exponential Augmented Lagrangian Method for Computing the Projection Robust Wasserstein Distance

Bo Jiang, Ya-Feng Liu

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design

Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Greg Farquhar

Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes

Jianqiao Sun, Yudi Su, Xinyang Liu, Zhibin Duan, Bo Chen

GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection

Jinggang Chen, Junjie Li, Xiaoyang Qu, Jianzong Wang, Jiguang Wan

Strategic Apple Tasting

Keegan Harris, Chara Podimata, Steven Z. Wu

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model

Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist

Online POMDP Planning with Anytime Deterministic Guarantees

Moran Barenboim, Vadim Indelman

DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu

Invariant Learning via Probability of Sufficient and Necessary Causes

Mengyue Yang, Zhen Fang, Yonggang Zhang, Yali Du, Furui Liu

Smoothed Analysis of Sequential Probability Assignment

Alankrita Bhatt, Nika Haghtalab, Abhishek Shetty

AQuA: A Benchmarking Tool for Label Quality Assessment

Mononito Goswami, Vedant Sanil, Arjun Choudhry, Arvind Srinivasan, Chalisa Udompanyawit

On Masked Pre-training and the Marginal Likelihood

Pablo Moreno-Muñoz, Pol Garcia Recasens, Søren Hauberg

SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process

Mengyu Wang, Henghui Ding, Jun Hao Liew, Jiajun Liu, Yao Zhao

FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks

Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong

Global Structure-Aware Diffusion Process for Low-light Image Enhancement

Jinhui HOU, Zhiyu Zhu, Junhui Hou, Hui LIU, Huanqiang Zeng

Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression

Jing Xu, Jiaye Teng, Yang Yuan, Andrew Yao

DeepSimHO: Stable Pose Estimation for Hand-Object Interaction via Physics Simulation

Rong Wang, Wei Mao, Hongdong Li

Sample-efficient Multi-objective Molecular Optimization with GFlowNets

Yiheng Zhu, Jialu Wu, Chaowen Hu, Jiahuan Yan, kim hsieh

On the Robustness of Removal-Based Feature Attributions

Chris Lin, Ian Covert, Su-in Lee

Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective

Zihan Luo, Hong Huang, Jianxun Lian, Xiran Song, Xing Xie

The Graph Pencil Method: Mapping Subgraph Densities to Stochastic Block Models

Lee Gunderson, Gecia Bravo-Hermsdorff, Peter Orbanz

One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation

Zhiwei Hao, Jianyuan Guo, Kai Han, Yehui Tang, Han Hu

RangePerception: Taming LiDAR Range View for Efficient and Accurate 3D Object Detection

Yeqi Bai, Ben Fei, Youquan Liu, Tao Ma, Yuenan Hou

Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths

Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Berend Ensing

On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds

David Woodruff, Fred Zhang, Samson Zhou

Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks

Matthew Farrugia-Roberts

Smooth, exact rotational symmetrization for deep learning on point clouds

Sergey Pozdnyakov, Michele Ceriotti

Auditing for Human Expertise

Rohan Alur, Loren Laine, Darrick Li, Manish Raghavan, Devavrat Shah

Faster Differentially Private Convex Optimization via Second-Order Methods

Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Guha Thakurta

CAST: Cross-Attention in Space and Time for Video Action Recognition

Dongho Lee, Jongseo Lee, Jinwoo Choi

Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses

Jacob Granley, Tristan Fauvel, Matthew Chalk, Michael Beyeler

NCDL: A Framework for Deep Learning on non-Cartesian Lattices

Joshua Horacsek, Usman Alim

Controlling Text-to-Image Diffusion by Orthogonal Finetuning

Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng

On the Role of Randomization in Adversarially Robust Classification

Lucas Gnecco Heredia, Muni Sreenivas Pydi, Laurent Meunier, Benjamin Negrevergne, Yann Chevaleyre

Diverse Shape Completion via Style Modulated Generative Adversarial Networks

Wesley Khademi, Fuxin Li

A unified framework for information-theoretic generalization bounds

Yifeng Chu, Maxim Raginsky

Imagine That! Abstract-to-Intricate Text-to-Image Synthesis with Scene Graph Hallucination Diffusion

Shengqiong Wu, Hao Fei, Hanwang Zhang, Tat-Seng Chua

Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models

Zhimin Chen, Longlong Jing, Yingwei Li, Bing Li

SE(3) Equivariant Augmented Coupling Flows

Laurence Midgley, Vincent Stimper, Javier Antoran, Emile Mathieu, Bernhard Schölkopf

Self-Correcting Bayesian Optimization through Bayesian Active Learning

Carl Hvarfner, Erik Hellsten, Frank Hutter, Luigi Nardi

The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data Only

Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Hamza Alobeidli

Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception

Hassan Akbari, Dan Kondratyuk, Yin Cui, Rachel Hornung, Huisheng Wang

Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation

Zihao Yue, Anwen Hu, Liang Zhang, Qin Jin

Learning Cuts via Enumeration Oracles

Daniel Thuerck, Boro Sofranac, Marc E Pfetsch, Sebastian Pokutta

Described Object Detection: Liberating Object Detection with Flexible Expressions

Chi Xie, Zhao Zhang, Yixuan Wu, Feng Zhu, Rui Zhao

Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning

Lin Guan, Karthik Valmeekam, Sarath Sreedharan, Subbarao Kambhampati

Improving Robustness with Adaptive Weight Decay

Mohammad Amin Ghiasi, Ali Shafahi, Reza Ardekani

DISCS: A Benchmark for Discrete Sampling

Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang

Diversify Your Vision Datasets with Automatic Diffusion-based Augmentation

Lisa Dunlap, Alyssa Umino, Han Zhang, Jiezhi Yang, Joseph E Gonzalez

Energy-Efficient Scheduling with Predictions

Eric Balkanski, Noemie Perivier, Clifford Stein, Hao-Ting Wei

Core-sets for Fair and Diverse Data Summarization

Sepideh Mahabadi, Stojan Trajanovski

D4Explainer: In-distribution Explanations of Graph Neural Network via Discrete Denoising Diffusion

Jialin Chen, Shirley Wu, Abhijit Gupta, Rex Ying

Generalized equivalences between subsampling and ridge regularization

Pratik Patil, Jin-Hong Du

CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference

Wenxuan Zeng, Meng Li, Haichuan Yang, Wen-jie Lu, Runsheng Wang

Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments

Dairui Wang, Junyu Cao, Yan Zhang, Wei Qi

Debiasing Conditional Stochastic Optimization

Lie He, Shiva P. Kasiviswanathan

CQM: Curriculum Reinforcement Learning with a Quantized World Model

Seungjae Lee, Daesol Cho, Jonghae Park, H. Jin Kim

MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers

LILI YU, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer

A polar prediction model for learning to represent visual transformations

Pierre-Étienne Fiquet, Eero P. Simoncelli

Multi-Agent Learning with Heterogeneous Linear Contextual Bandits

Anh Do, Thanh Nguyen-Tang, Raman Arora

Neural Processes with Stability

Huafeng Liu, Liping Jing, Jian Yu

T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation

Kaiyi Huang, Kaiyue Sun, Enze Xie, Zhenguo Li, Xihui Liu

Bounding training data reconstruction in DP-SGD

Jamie Hayes, Borja Balle, Saeed Mahloujifar

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization

Hao Dong, Ismail Nejjar, Han Sun, Eleni Chatzi, Olga Fink