NeurIPS 2023

3,540 papers

LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day

Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu

A Measure-Theoretic Axiomatisation of Causality

Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet

Relax, it doesn’t matter how you get there: A new self-supervised approach for multi-timescale behavior analysis

Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor

Train 'n Trade: Foundations of Parameter Markets

Tzu-Heng Huang, Harit Vishwakarma, Frederic Sala

Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow

Sizhe Wei, Yuxi Wei, Yue Hu, Yifan Lu, Yiqi Zhong

Byzantine-Tolerant Methods for Distributed Variational Inequalities

Nazarii Tupitsa, Abdulla Jasem Almansoori, Yanlin Wu, Martin Takac, Karthik Nandakumar

PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning.

Mingjia Shi, Yuhao Zhou, Kai Wang, Huaizheng Zhang, Shudong Huang

Learning Layer-wise Equivariances Automatically using Gradients

Tycho van der Ouderaa, Alexander Immer, Mark van der Wilk

Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting

Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang

Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning

Hongyu Zang, Xin Li, Leiji Zhang, Yang Liu, Baigui Sun

Video Timeline Modeling For News Story Understanding

Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang

Counterfactually Comparing Abstaining Classifiers

Yo Joong Choe, Aditya Gangrade, Aaditya Ramdas

Polynomial-Time Linear-Swap Regret Minimization in Imperfect-Information Sequential Games

Gabriele Farina, Charilaos Pipis

Learning to Discover Skills through Guidance

HYUNSEUNG KIM, BYUNG KUN LEE, Hojoon Lee, Dongyoon Hwang, Sejik Park

Practical Differentially Private Hyperparameter Tuning with Subsampling

Antti Koskela, Tejas D Kulkarni

TransHP: Image Classification with Hierarchical Prompting

Wenhao Wang, Yifan Sun, Wei Li, Yi Yang

Rewiring Neurons in Non-Stationary Environments

Zhicheng Sun, Yadong Mu

Topological Parallax: A Geometric Specification for Deep Perception Models

Abraham Smith, Michael Catanzaro, Gabrielle Angeloro, Nirav Patel, Paul Bendich

Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs

CHEN SHENGYUAN, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun

MultiMoDN—Multimodal, Multi-Task, Interpretable Modular Networks

Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels

Mind2Web: Towards a Generalist Agent for the Web

Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Sam Stevens

Emergent and Predictable Memorization in Large Language Models

Stella Biderman, USVSN PRASHANTH, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony

Two Sides of The Same Coin: Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation

Shutong Ding, Tianyu Cui, Jingya Wang, Ye Shi

What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models

Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank Reddi, Stefanie Jegelka

Scalable Transformer for PDE Surrogate Modeling

Zijie Li, Dule Shu, Amir Barati Farimani

Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions

Leonidas Tsepenekas, Ivan Brugere, Freddy Lecue, Daniele Magazzeni

High-Fidelity Audio Compression with Improved RVQGAN

Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, Ishaan Kumar, Kundan Kumar

Lending Interaction Wings to Recommender Systems with Conversational Agents

Jiarui Jin, Xianyu Chen, Fanghua Ye, Mengyue Yang, Yue Feng

LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

Duy M. H. Nguyen, Hoang Nguyen, Nghiem Diep, Tan Ngoc Pham, Tri Cao

Convolutional Visual Prompt for Robust Visual Perception

Yun-Yun Tsai, Chengzhi Mao, Junfeng Yang

Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models

Yeongbin Kim, Gautam Singh, Junyeong Park, Caglar Gulcehre, Sungjin Ahn

When is Agnostic Reinforcement Learning Statistically Tractable?

Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro

The Transient Nature of Emergent In-Context Learning in Transformers

Aaditya Singh, Stephanie Chan, Ted Moskovitz, Erin Grant, Andrew Saxe

On the Importance of Feature Separability in Predicting Out-Of-Distribution Error

RENCHUNZI XIE, Hongxin Wei, Lei Feng, Yuzhou Cao, Bo An

A Unified Framework for U-Net Design and Analysis

Christopher K. I. Williams, Fabian Falck, George Deligiannidis, Chris C Holmes, Arnaud Doucet

Mathematical Capabilities of ChatGPT

Simon Frieder, Luca Pinchetti, Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori

Leveraging sparse and shared feature activations for disentangled representation learning

Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà

Certification of Distributional Individual Fairness

Matthew Wicker, Vihari Piratla, Adrian Weller

Training neural operators to preserve invariant measures of chaotic attractors

Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett

D-CIPHER: Discovery of Closed-form Partial Differential Equations

Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar

On Sparse Modern Hopfield Model

Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen

trajdata: A Unified Interface to Multiple Human Trajectory Datasets

Boris Ivanovic, Guanyu Song, Igor Gilitschenski, Marco Pavone

Theoretical and Practical Perspectives on what Influence Functions Do

Andrea Schioppa, Katja Filippova, Ivan Titov, Polina Zablotskaia

Energy Transformer

Benjamin Hoover, Yuchen Liang, Bao Pham, Rameswar Panda, Hendrik Strobelt

ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors

Xiaoxuan Ma, Stephan Kaufhold, Jiajun Su, Wentao Zhu, Jack Terwilliger

Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense

Kalpesh Krishna, Yixiao Song, Marzena Karpinska, John Wieting, Mohit Iyyer

On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm

Qi Chen, Changjian Shui, Ligong Han, Mario Marchand

A Single 2D Pose with Context is Worth Hundreds for 3D Human Pose Estimation

Qitao Zhao, Ce Zheng, Mengyuan Liu, Chen Chen

Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework

Paul Pu Liang, Yun Cheng, Xiang Fan, Chun Kai Ling, Suzanne Nie

Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information

Arman Zharmagambetov, Brandon Amos, Aaron Ferber, Taoan Huang, Bistra Dilkina

Regularizing Neural Networks with Meta-Learning Generative Models

Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima

Canonical normalizing flows for manifold learning

Kyriakos Flouris, Ender Konukoglu

SQ Lower Bounds for Learning Mixtures of Linear Classifiers

Ilias Diakonikolas, Daniel Kane, Yuxin Sun

Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems

Samuel Hurault, Ulugbek Kamilov, Arthur Leclaire, Nicolas Papadakis

The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks

Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas

Addressing Negative Transfer in Diffusion Models

Hyojun Go, Kim, Yunsung Lee, Seunghyun Lee, Shinhyeok Oh

Self-Predictive Universal AI

Elliot Catt, Jordi Grau-moya, Marcus Hutter, Matthew Aitchison, Tim Genewein

Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning

Yue Tan, Chen Chen, Weiming Zhuang, Xin Dong, Lingjuan Lyu

STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning

Weipu Zhang, Gang Wang, Jian Sun, Yetian Yuan, Gao Huang

On Computing Pairwise Statistics with Local Differential Privacy

Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Adam Sealfon

p-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison

Kai Klede, Thomas Altstidl, Dario Zanca, Bjoern Eskofier

DataComp: In search of the next generation of multimodal datasets

Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis

Adapting Neural Link Predictors for Data-Efficient Complex Query Answering

Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, Isabelle Augenstein

DISCOVER: Making Vision Networks Interpretable via Competition and Dissection

Konstantinos Panousis, Sotirios Chatzis

Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions

Hao Wang, Luxi He, RUI GAO, Flavio Calmon

Active Learning for Semantic Segmentation with Multi-class Label Query

SEHYUN HWANG, Sohyun Lee, Hoyoung Kim, Minhyeon Oh, Jungseul Ok

Hyper-HMM: aligning human brains and semantic features in a common latent event space

Caroline Lee, Jane Han, Ma Feilong, Guo Jiahui, James Haxby

Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation

Zhongqi Yue, Qianru Sun, Hanwang Zhang

Auxiliary Losses for Learning Generalizable Concept-based Models

Ivaxi Sheth, Samira Ebrahimi Kahou

Contextual Gaussian Process Bandits with Neural Networks

Haoting Zhang, Jinghai He, Rhonda Righter, Zuo-Jun Shen, Zeyu Zheng

The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data

Peter Nickl, Lu Xu, Dharmesh Tailor, Thomas Möllenhoff, Mohammad Emtiyaz Khan

VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models

Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu

Use perturbations when learning from explanations

Juyeon Heo, Vihari Piratla, Matthew Wicker, Adrian Weller

Bringing regularized optimal transport to lightspeed: a splitting method adapted for GPUs

Jacob Lindbäck, Zesen Wang, Mikael Johansson

A Finite-Particle Convergence Rate for Stein Variational Gradient Descent

Jiaxin Shi, Lester W. Mackey

Causal Imitability Under Context-Specific Independence Relations

Fateme Jamshidi, Sina Akbari, Negar Kiyavash

How many samples are needed to leverage smoothness?

Vivien Cabannes, Stefano Vigogna

Multi Time Scale World Models

Vaisakh Shaj Kumar, SALEH GHOLAM ZADEH, Ozan Demir, Luiz Douat, Gerhard Neumann

VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation

Zekun Qi, Muzhou Yu, Runpei Dong, Kaisheng Ma

EMBERSim: A Large-Scale Databank for Boosting Similarity Search in Malware Analysis

Dragos Georgian Corlatescu, Alexandru Dinu, Mihaela Petruta Gaman, Paul Sumedrea

Uncertainty Quantification over Graph with Conformalized Graph Neural Networks

Kexin Huang, Ying Jin, Emmanuel Candes, Jure Leskovec

Likelihood Ratio Confidence Sets for Sequential Decision Making

Nicolas Emmenegger, Mojmir Mutny, Andreas Krause

LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark

Zhenfei Yin, Jiong Wang, Jianjian Cao, Zhelun Shi, Dingning Liu

Towards Test-Time Refusals via Concept Negation

Peiran Dong, Song Guo, Junxiao Wang, Bingjie WANG, Jiewei Zhang

Posterior Sampling for Competitive RL: Function Approximation and Partial Observation

Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang

Sorting with Predictions

Xingjian Bai, Christian Coester

Learning from Both Structural and Textual Knowledge for Inductive Knowledge Graph Completion

Kunxun Qi, Jianfeng Du, Hai Wan

On the Ability of Graph Neural Networks to Model Interactions Between Vertices

Noam Razin, Tom Verbin, Nadav Cohen

EPIC Fields: Marrying 3D Geometry and Video Understanding

Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu, David Fouhey, Iro Laina

Strategic Classification under Unknown Personalized Manipulation

Han Shao, Avrim Blum, Omar Montasser

Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release

Abhishek Singh, Praneeth Vepakomma, Vivek Sharma, Ramesh Raskar

SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation

Zhuoyan Luo, Yicheng Xiao, Yong Liu, Shuyan Li, Yitong Wang

Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction

Xiaowen Jiang, Sebastian U Stich

Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States

Valerii Iakovlev, Markus Heinonen, Harri Lahdesmaki

High dimensional, tabular deep learning with an auxiliary knowledge graph

Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec

Wasserstein distributional robustness of neural networks

Xingjian Bai, Guangyi He, Yifan Jiang, Jan Obloj

Brant: Foundation Model for Intracranial Neural Signal

Daoze Zhang, Zhizhang Yuan, Yang Yang, Junru Chen, Jingjing Wang

Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing

Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt, Joost van de Weijer

Making Scalable Meta Learning Practical

Sang Choe, Sanket Vaibhav Mehta, Hwijeen Ahn, Willie Neiswanger, Pengtao Xie

Online Convex Optimization with Unbounded Memory

Raunak Kumar, Sarah Dean, Robert D. Kleinberg