NeurIPS 2023

3,540 papers

On quantum backpropagation, information reuse, and cheating measurement collapse

Amira Abbas, Robbie King, Hsin-Yuan Huang, Ramis Movassagh, Dar Gilboa

LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

Bo Liu, Yifeng Zhu, Chongkai Gao, Yihao Feng, Qiang Liu

Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering

Noah Hollmann, Samuel Müller, Frank Hutter

Sounding Bodies: Modeling 3D Spatial Sound of Humans Using Body Pose and Audio

Xudong XU, Dejan Markovic, Jacob Sandakly, Todd Keebler, Steven Krenn

Optimal Learners for Realizable Regression: PAC Learning and Online Learning

Idan Attias, Steve Hanneke, Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas

iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models

Tianyu Chen, Kevin Bello, Bryon Aragam, Pradeep K Ravikumar, Pradeep K. Ravikumar

DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework

Siran Dai, Qianqian Xu, Zhiyong Yang, Xiaochun Cao, Qingming Huang

On the Convergence of Black-Box Variational Inference

Kyurae Kim, Jisu Oh, Kaiwen Wu, Yian Ma, Jacob Gardner

DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening

Bowen Gao, Bo Qiang, Haichuan Tan, Yinjun Jia, Minsi Ren

Modulated Neural ODEs

Ilze Amanda Auzina, Çağatay Yıldız, Sara Magliacane, Matthias Bethge, Efstratios Gavves

PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection

Qiang Zhou, Weize Li, Lihan Jiang, Guoliang Wang, Guyue Zhou

On Separate Normalization in Self-supervised Transformers

Xiaohui Chen, Yinkai Wang, Yuanqi Du, Soha Hassoun, Liping Liu

AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs

Adam Cobb, Anirban Roy, Daniel Elenius, Frederick Heim, Brian Swenson

FELM: Benchmarking Factuality Evaluation of Large Language Models

shiqi chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao

Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach

Nurendra Choudhary, Nikhil Rao, Chandan Reddy

SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities

Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty

Thought Cloning: Learning to Think while Acting by Imitating Human Thinking

Shengran Hu, Jeff Clune

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks

Jimmy Di, Jack Douglas, Jayadev Acharya, Gautam Kamath, Ayush Sekhari

DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models

Tsun-Hsuan Johnson Wang, Juntian Zheng, Pingchuan Ma, Yilun Du, Byungchul Kim

Students Parrot Their Teachers: Membership Inference on Model Distillation

Matthew Jagielski, Milad Nasr, Katherine Lee, Christopher A. Choquette-Choo, Nicholas Carlini

Transportability for Bandits with Data from Different Environments

Alexis Bellot, Alan Malek, Silvia Chiappa

Sequential Memory with Temporal Predictive Coding

Mufeng Tang, Helen Barron, Rafal Bogacz

RoboHive: A Unified Framework for Robot Learning

Vikash Kumar, Rutav Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano

Information Geometry of the Retinal Representation Manifold

Xuehao Ding, Dongsoo Lee, Joshua Melander, George Sivulka, Surya Ganguli

Detecting hidden confounding in observational data using multiple environments

Rickard Karlsson, Jesse Krijthe

LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Neel Guha, Julian Nyarko, Daniel Ho, Christopher Re, Adam Chilton

Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability

Usha Bhalla, Suraj Srinivas, Himabindu Lakkaraju

Domain Adaptive Imitation Learning with Visual Observation

Sungho Choi, Seungyul Han, Woojun Kim, Jongseong Chae, Whiyoung Jung

GlyphControl: Glyph Conditional Control for Visual Text Generation

Yukang Yang, Dongnan Gui, YUHUI YUAN, WEICONG LIANG, Haisong Ding

Training Neural Networks is NP-Hard in Fixed Dimension

Vincent Froese, Christoph Hertrich

SODA: Robust Training of Test-Time Data Adaptors

Zige Wang, Yonggang Zhang, Zhen Fang, Long Lan, Wenjing Yang

Adaptive Online Replanning with Diffusion Models

Siyuan Zhou, Yilun Du, Shun Zhang, Mengdi Xu, Yikang Shen

MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability

Fabien Casenave, Brian Staber, Xavier Roynard

Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games

Youbang Sun, Tao Liu, Ruida Zhou, P. R. Kumar, Shahin Shahrampour

Weakly Coupled Deep Q-Networks

Ibrahim El Shar, Daniel Jiang

Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language.

Eghbal Hosseini, Evelina Fedorenko

CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra

Andres Potapczynski, Marc Finzi, Geoff Pleiss, Andrew G Wilson

Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach

Urte Adomaityte, Gabriele Sicuro, Pierpaolo Vivo

LayoutPrompter: Awaken the Design Ability of Large Language Models

Jiawei Lin, Jiaqi Guo, Shizhao Sun, Zijiang Yang, Jian-Guang Lou

Training Energy-Based Normalizing Flow with Score-Matching Objectives

Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, Zsolt Kira, Chun-Yi Lee

Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge

Abhin Shah, Karthikeyan Shanmugam, Murat Kocaoglu

Lift Yourself Up: Retrieval-augmented Text Generation with Self-Memory

Xin Cheng, Di Luo, Xiuying Chen, Lemao Liu, Dongyan Zhao

Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data

Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song

LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer

Haoyu Chen, Hao Tang, Radu Timofte, Luc V Gool, Guoying Zhao

Offline Imitation Learning with Variational Counterfactual Reasoning

Zexu Sun, Bowei He, Jinxin Liu, Xu Chen, Chen Ma

DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

Haoran Ye, Jiarui Wang, Zhiguang Cao, Helan Liang, Yong Li

Decision Tree for Locally Private Estimation with Public Data

Yuheng Ma, Han Zhang, Yuchao Cai, Hanfang Yang

Intervention Generalization: A View from Factor Graph Models

Gecia Bravo-Hermsdorff, David Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva

Constant Approximation for Individual Preference Stable Clustering

Anders Aamand, Justin Chen, Allen Liu, Sandeep Silwal, Pattara Sukprasert

History Filtering in Imperfect Information Games: Algorithms and Complexity

Christopher Solinas, Doug Rebstock, Nathan Sturtevant, Michael Buro

D-Separation for Causal Self-Explanation

Wei Liu, Jun Wang, Haozhao Wang, Ruixuan Li, Zhiying Deng

A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset

Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum

FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning

Kun Song, Huimin Ma, Bochao Zou, Huishuai Zhang, Weiran Huang

Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions

Dongjie Wang, Meng Xiao, Min Wu, pengfei wang, Yuanchun Zhou

Differentially Private Approximate Near Neighbor Counting in High Dimensions

Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi, Shyam Narayanan

Progressive Ensemble Distillation: Building Ensembles for Efficient Inference

Don Dennis, Abhishek Shetty, Anish Prasad Sevekari, Kazuhito Koishida, Virginia Smith

Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction

Zuobai Zhang, Minghao Xu, Aurelie C. Lozano, Vijil Chenthamarakshan, Payel Das

Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels

Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li

Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models

Pan Lu, Baolin Peng, Hao Cheng, Michel Galley, Kai-Wei Chang

“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization

Shuang Li, Ke Li, Wei Li

Causal Discovery from Subsampled Time Series with Proxy Variables

Mingzhou Liu, Xinwei Sun, Lingjing Hu, Yizhou Wang

Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression

Ilias Diakonikolas, Daniel Kane, Ankit Pensia, Thanasis Pittas

Parameterizing Non-Parametric Meta-Reinforcement Learning Tasks via Subtask Decomposition

Suyoung Lee, Myungsik Cho, Youngchul Sung

One Fits All: Power General Time Series Analysis by Pretrained LM

Tian Zhou, Peisong Niu, xue wang, Liang Sun, Rong Jin

BiMatting: Efficient Video Matting via Binarization

Haotong Qin, Lei Ke, Xudong Ma, Martin Danelljan, Yu-Wing Tai

Robust Concept Erasure via Kernelized Rate-Distortion Maximization

Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Amr Ahmed, Snigdha Chaturvedi

Model Shapley: Equitable Model Valuation with Black-box Access

Xinyi Xu, Thanh Lam, Chuan Sheng Foo, Bryan Kian Hsiang Low

Learning a 1-layer conditional generative model in total variation

Ajil Jalal, Justin Kang, Ananya Uppal, Kannan Ramchandran, ecprice

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution

Eric Nguyen, Michael Poli, Marjan Faizi, Armin Thomas, Michael Wornow

Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs

Lin Yang, Junlong Lyu, Wenlong Lyu, Zhitang Chen

Fairness-guided Few-shot Prompting for Large Language Models

Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu, Zhirui Zhang

An Inductive Bias for Tabular Deep Learning

Ege Beyazit, Jonathan Kozaczuk, Bo Li, Vanessa Wallace, Bilal Fadlallah

Structured Federated Learning through Clustered Additive Modeling

Jie Ma, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

L2T-DLN: Learning to Teach with Dynamic Loss Network

Zhaoyang Hai, Liyuan Pan, Xiabi Liu, Zhengzheng Liu, Mirna Yunita

Supervised Pretraining Can Learn In-Context Reinforcement Learning

Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn

RIO: A Benchmark for Reasoning Intention-Oriented Objects in Open Environments

Mengxue Qu, Yu Wu, Wu Liu, Xiaodan Liang, Jingkuan Song

Bayesian Optimisation of Functions on Graphs

Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne

Unlocking Deterministic Robustness Certification on ImageNet

Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson

UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild

Can Qin, Shu Zhang, Ning Yu, Yihao Feng, Xinyi Yang

Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense

Zunzhi You, Daochang Liu, Bohyung Han, Chang Xu

SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning

Sarp Aykent, Tian Xia

Training Transitive and Commutative Multimodal Transformers with LoReTTa

Manuel Tran, Yashin Dicente Cid, Amal Lahiani, Fabian J. Theis, Tingying Peng

Mirror Diffusion Models for Constrained and Watermarked Generation

Guan-Horng Liu, Tianrong Chen, Evangelos Theodorou, Molei Tao

Learning Curves for Deep Structured Gaussian Feature Models

Jacob Zavatone-Veth, Cengiz Pehlevan

Benchmarking Robustness to Adversarial Image Obfuscations

Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu

Differentiable and Stable Long-Range Tracking of Multiple Posterior Modes

Ali Younis, Erik B. Sudderth

Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning

Casey Meehan, Florian Bordes, Pascal Vincent, Kamalika Chaudhuri, Chuan Guo

Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data

Saptarshi Roy, Raymond K. W. Wong, Yang Ni

Perception Test: A Diagnostic Benchmark for Multimodal Video Models

Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adria Recasens, Larisa Markeeva

Learning Energy-Based Prior Model with Diffusion-Amortized MCMC

Peiyu Yu, Yaxuan Zhu, Sirui Xie, Xiaojian (Shawn) Ma, Ruiqi Gao

Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone

Zeyinzi Jiang, Chaojie Mao, Ziyuan Huang, Ao Ma, Yiliang Lv

Focused Transformer: Contrastive Training for Context Scaling

Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski

Break It Down: Evidence for Structural Compositionality in Neural Networks

Michael Lepori, Thomas Serre, Ellie Pavlick

Precise asymptotic generalization for multiclass classification with overparameterized linear models

David Wu, Anant Sahai

Online Ad Procurement in Non-stationary Autobidding Worlds

Jason Cheuk Nam Liang, Haihao Lu, Baoyu Zhou

Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem

Tal Amir, Steven Gortler, Ilai Avni, Ravina Ravina, Nadav Dym

Intelligent Knee Sleeves: A Real-time Multimodal Dataset for 3D Lower Body Motion Estimation Using Smart Textile

Wenwen Zhang, Arvin Tashakori, Zenan Jiang, Amir Servati, Harishkumar Narayana

Norm-based Generalization Bounds for Sparse Neural Networks

Tomer Galanti, Mengjia Xu, Liane Galanti, Tomaso Poggio

Lie Point Symmetry and Physics-Informed Networks

Tara Akhound-Sadegh, Laurence Perreault-Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh

Generalized Belief Transport

Junqi Wang, Pei Wang, Patrick Shafto