ICLR 2024

2,260 papers

AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?

Qi Zhao, Shijie Wang, Ce Zhang, Changcheng Fu, Minh Quan Do

VeRA: Vector-based Random Matrix Adaptation

Dawid Jan Kopiczko, Tijmen Blankevoort, Yuki M Asano

PerceptionCLIP: Visual Classification by Inferring and Conditioning on Contexts

Bang An, Sicheng Zhu, Michael-Andrei Panaitescu-Liess, Chaithanya Kumar Mummadi, Furong Huang

Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?

Yu-Lin Tsai, Chia-Yi Hsu, Chulin Xie, Chih-Hsun Lin, Jia You Chen

Object-Centric Learning with Slot Mixture Module

Daniil Kirilenko, Vitaliy Vorobyov, Alexey Kovalev, Aleksandr Panov

Orbit-Equivariant Graph Neural Networks

Matthew Morris, Bernardo Cuenca Grau, Ian Horrocks

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang

Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models

Tianzhe Chu, Shengbang Tong, Tianjiao Ding, xili dai, Benjamin David Haeffele

TRAM: Bridging Trust Regions and Sharpness Aware Minimization

Tom Sherborne, Naomi Saphra, Pradeep Dasigi, Hao Peng

Lifting Architectural Constraints of Injective Flows

Peter Sorrenson, Felix Draxler, Armand Rousselot, Sander Hummerich, Lea Zimmermann

Provably Efficient UCB-type Algorithms For Learning Predictive State Representations

Ruiquan Huang, Yingbin Liang, Jing Yang

On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods

Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji

Non-Exchangeable Conformal Risk Control

António Farinhas, Chrysoula Zerva, Dennis Thomas Ulmer, Andre Martins

Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck

Marco Federici, Patrick Forré, Ryota Tomioka, Bastiaan S. Veeling

Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space

Hao Xiong, Yehui Tang, Yunlin He, Wei Tan, Junchi Yan

Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?

Gourav Datta, Zeyu Liu, Peter Anthony Beerel

Emergent Communication with Conversational Repair

Mitja Nikolaus

Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning

Ge Li, Hongyi Zhou, Dominik Roth, Serge Thilges, Fabian Otto

Retrieval-based Disentangled Representation Learning with Natural Language Supervision

Jiawei Zhou, Xiaoguang Li, Lifeng Shang, Xin Jiang, Qun Liu

Time-Efficient Reinforcement Learning with Stochastic Stateful Policies

Firas Al-Hafez, Guoping Zhao, Jan Peters, Davide Tateo

A Topological Perspective on Demystifying GNN-Based Link Prediction Performance

Yu Wang, Tong Zhao, Yuying Zhao, Yunchao Liu, Xueqi Cheng

EQA-MX: Embodied Question Answering using Multimodal Expression

Md Mofijul Islam, Alexi Gladstone, Riashat Islam, Tariq Iqbal

Neural Optimal Transport with General Cost Functionals

Arip Asadulaev, Alexander Korotin, Vage Egiazarian, Petr Mokrov, Evgeny Burnaev

Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime

Keita Suzuki, Taiji Suzuki

Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning

Maxime Wabartha, Joelle Pineau

Variational Bayesian Last Layers

James Harrison, John Willes, Jasper Snoek

Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks

Xu Zheng, Farhad Shirani, Tianchun Wang, Wei Cheng, Zhuomin Chen

Towards Robust Offline Reinforcement Learning under Diverse Data Corruption

Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang

TorchRL: A data-driven decision-making library for PyTorch

Albert Bou, Matteo Bettini, Sebastian Dittert, Vikash Kumar, Shagun Sodhani

BEND: Benchmarking DNA Language Models on Biologically Meaningful Tasks

Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz

On the Provable Advantage of Unsupervised Pretraining

Jiawei Ge, Shange Tang, Jianqing Fan, Chi Jin

Subtractive Mixture Models via Squaring: Representation and Learning

Lorenzo Loconte, Aleksanteri Mikulus Sladek, Stefan Mengel, Martin Trapp, Arno Solin

From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module

Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael M. Bronstein, Simone Scardapane

Better Neural PDE Solvers Through Data-Free Mesh Movers

Peiyan Hu, Yue Wang, Zhi-ming Ma

Conditional Variational Diffusion Models

Gabriel della Maggiora, Luis Alberto Croquevielle, Nikita Deshpande, Harry Horsley, Thomas Heinis

Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP

Zixiang Chen, Yihe Deng, Yuanzhi Li, Quanquan Gu

Replay across Experiments: A Natural Extension of Off-Policy RL

Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen, Tuomas Haarnoja, Sandy Huang

OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text

Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba

Solving High Frequency and Multi-Scale PDEs with Gaussian Processes

Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby

Robust Model-Based Optimization for Challenging Fitness Landscapes

Saba Ghaffari, Ehsan Saleh, Alex Schwing, Yu-Xiong Wang, Martin D. Burke

A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines

Manju Garimella, Denizhan Pak, Justin Newell Wood, Samantha Marie Waters Wood

S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic

Safa Messaoud, Billel Mokeddem, Zhenghai Xue, Linsey Pang, Bo An

Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response

Junfeng Long, Zirui Wang, Quanyi Li, Liu Cao, Jiawei Gao

Implicit Maximum a Posteriori Filtering via Adaptive Optimization

Gianluca Bencomo, Jake Snell, Thomas L. Griffiths

On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning

Rohan Subramani, Marcus Williams, Max Heitmann, Halfdan Holm, Charlie Griffin

Learning from Sparse Offline Datasets via Conservative Density Estimation

Zhepeng Cen, ZUXIN LIU, Zitong Wang, Yihang Yao, Henry Lam

Quality-Diversity through AI Feedback

Herbie Bradley, Andrew Dai, Hannah Benita Teufel, Jenny Zhang, Koen Oostermeijer

AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images

Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi, Viraj Uday Prabhu, Judy Hoffman

VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition

Chenyu Liu, XINLIANG ZHOU, Zhengri Zhu, Liming Zhai, Ziyu Jia

Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data

Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu

Chain of Log-Concave Markov Chains

Saeed Saremi, Ji Won Park, Francis Bach

OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning

Wei-Cheng Huang, Chun-Fu Chen, Hsiang Hsu

Generative Modeling with Phase Stochastic Bridge

Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos Theodorou, Joshua M. Susskind

Linearity of Relation Decoding in Transformer Language Models

Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg

Sparse Autoencoders Find Highly Interpretable Features in Language Models

Robert Huben, Hoagy Cunningham, Logan Riggs Smith, Aidan Ewart, Lee Sharkey

Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games

Stephen Marcus McAleer, JB Lanier, Kevin A. Wang, Pierre Baldi, Tuomas Sandholm

Lagrangian Flow Networks for Conservation Laws

Fabricio Arend Torres, Marcello Massimo Negri, Marco Inversi, Jonathan Aellen, Volker Roth

Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners

Sarthak Yadav, Sergios Theodoridis, Lars Kai Hansen, Zheng-Hua Tan

FeatUp: A Model-Agnostic Framework for Features at Any Resolution

Stephanie Fu, Mark Hamilton, Laura E. Brandt, Axel Feldmann, Zhoutong Zhang

Pre-training with Random Orthogonal Projection Image Modeling

Maryam Haghighat, Peyman Moghadam, Shaheer Mohamed, Piotr Koniusz

Functional Interpolation for Relative Positions improves Long Context Transformers

Shanda Li, Chong You, Guru Guruganesh, Joshua Ainslie, Santiago Ontanon

Accelerating Sinkhorn algorithm with sparse Newton iterations

Xun Tang, Michael Shavlovsky, Holakou Rahmanian, Elisa Tardini, Kiran Koshy Thekumparampil

YaRN: Efficient Context Window Extension of Large Language Models

Bowen Peng, Jeffrey Quesnelle, Honglu Fan, Enrico Shippole

Privately Aligning Language Models with Reinforcement Learning

Fan Wu, Huseyin A Inan, Arturs Backurs, Varun Chandrasekaran, Janardhan Kulkarni

Sharpness-Aware Data Poisoning Attack

Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng

Post-hoc bias scoring is optimal for fair classification

Wenlong Chen, Yegor Klochkov, Yang Liu

Talk like a Graph: Encoding Graphs for Large Language Models

Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

Think before you speak: Training Language Models With Pause Tokens

Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar

A Characterization Theorem for Equivariant Networks with Point-wise Activations

Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin

Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection

Fan Shi, Bin Li, Xiangyang Xue

When can transformers reason with abstract symbols?

Enric Boix-Adsera, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin

Nougat: Neural Optical Understanding for Academic Documents

Lukas Blecher, Guillem Cucurull, Thomas Scialom, Robert Stojnic

T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Pratyush Maini, Sachin Goyal, Zachary Chase Lipton, J Zico Kolter, Aditi Raghunathan

Evaluating Representation Learning on the Protein Structure Universe

Arian Rokkum Jamasb, Alex Morehead, Chaitanya K. Joshi, Zuobai Zhang, Kieran Didi

Quadratic models for understanding catapult dynamics of neural networks

Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin

LLM Augmented LLMs: Expanding Capabilities through Composition

Rachit Bansal, Bidisha Samanta, Siddharth Dalmia, Nitish Gupta, Sriram Ganapathy

Estimating Conditional Mutual Information for Dynamic Feature Selection

Soham Gadgil, Ian Connick Covert, Su-in Lee

Reconciling Spatial and Temporal Abstractions for Goal Representation

Mehdi Zadem, Sergio Mover, Sao Mai Nguyen

Towards Diverse Behaviors: A Benchmark for Imitation Learning with Human Demonstrations

Xiaogang Jia, Denis Blessing, Xinkai Jiang, Moritz Reuss, Atalay Donat

Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective

Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo

Transformers can optimally learn regression mixture models

Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das

Optimal Sample Complexity of Contrastive Learning

Noga Alon, Dmitrii Avdiukhin, Dor Elboim, Orr Fischer, Grigory Yaroslavtsev

Mixture of Weak and Strong Experts on Graphs

Hanqing Zeng, Hanjia Lyu, Diyi Hu, Yinglong Xia, Jiebo Luo

Learning Polynomial Problems with SL(2, R)-Equivariance

Hannah Lawrence, Mitchell Tong Harris

Towards Principled Representation Learning from Videos for Reinforcement Learning

Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford

The Marginal Value of Momentum for Small Learning Rate SGD

Runzhe Wang, Sadhika Malladi, Tianhao Wang, Kaifeng Lyu, Zhiyuan Li

Language Model Cascades: Token-Level Uncertainty And Beyond

Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum, Ankit Singh Rawat, Aditya Krishna Menon

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning

Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

Grokking as the transition from lazy to rich training dynamics

Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan

Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models

Zeyu Zhou, Ruqi Bai, Sean Kulinski, Murat Kocaoglu, David I. Inouye

Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers

Oren Mangoubi, Nisheeth K. Vishnoi

Causally Aligned Curriculum Learning

Mingxuan Li, Junzhe Zhang, Elias Bareinboim

Differentiable Euler Characteristic Transforms for Shape Classification

Ernst Röell, Bastian Rieck

Searching for High-Value Molecules Using Reinforcement Learning and Transformers

Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX

Clément Bonnet, Daniel Luo, Donal John Byrne, Shikha Surana, Sasha Abramowitz

Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data

Yongsheng Mei, Mahdi Imani, Tian Lan

Quantifying the Plausibility of Context Reliance in Neural Machine Translation

Gabriele Sarti, Grzegorz Chrupała, Malvina Nissim, Arianna Bisazza

Towards Establishing Guaranteed Error for Learned Database Operations

Sepanta Zeighami, Cyrus Shahabi

"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection

Anshuman Chhabra, Peizhao Li, Prasant Mohapatra, Hongfu Liu

MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, Mohamed Elhoseiny