ICLR 2024

2,260 papers

Discovering Temporally-Aware Reinforcement Learning Algorithms

Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson

The Alignment Problem from a Deep Learning Perspective

Richard Ngo, Lawrence Chan, Sören Mindermann

Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms

Bowen Jing, Tommi S. Jaakkola, Bonnie Berger

Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark

Yehui Tang, Hao Xiong, Nianzu Yang, Tailong Xiao, Junchi Yan

Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Ruizhe Shi, Yuyao Liu, Yanjie Ze, Simon Shaolei Du, Huazhe Xu

Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders

Emanuele Palumbo, Laura Manduchi, Sonia Laguna, Daphné Chopard, Julia E Vogt

Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI

Weibang Jiang, Liming Zhao, Bao-Liang Lu

Unraveling the Key Components of OOD Generalization via Diversification

Harold Luc Benoit, Liangze Jiang, Andrei Atanov, Oğuzhan Fatih Kar, Mattia Rigotti

CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction

Size Wu, Wenwei Zhang, Lumin Xu, Sheng Jin, Xiangtai Li

Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach

Christian Fabian, Kai Cui, Heinz Koeppl

FOSI: Hybrid First and Second Order Optimization

Hadar Sivan, Moshe Gabel, Assaf Schuster

A differentiable brain simulator bridging brain simulation and brain-inspired computing

Chaoming Wang, Tianqiu Zhang, Sichao He, Hongyaoxing Gu, Shangyang Li

GAIA: a benchmark for General AI Assistants

Grégoire Mialon, Clémentine Fourrier, Thomas Wolf, Yann LeCun, Thomas Scialom

STARC: A General Framework For Quantifying Differences Between Reward Functions

Joar Max Viktor Skalse, Lucy Farnik, Sumeet Ramesh Motwani, Erik Jenner, Adam Gleave

Neural structure learning with stochastic differential equations

Benjie Wang, Joel Jennings, Wenbo Gong

An Extensible Framework for Open Heterogeneous Collaborative Perception

Yifan Lu, Yue Hu, Yiqi Zhong, Dequan Wang, Yanfeng Wang

Off-Policy Primal-Dual Safe Reinforcement Learning

Zifan Wu, Bo Tang, Qian Lin, Chao Yu, Shangqin Mao

Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data

Antonis Antoniades, Yiyi Yu, Joe S Canzano, William Yang Wang, Spencer Smith

UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition

Wenxuan Zhou, Sheng Zhang, Yu Gu, Muhao Chen, Hoifung Poon

Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data

Ayesha Vermani, Il Memming Park, Josue Nassar

Multilinear Operator Networks

Yixin Cheng, Grigorios Chrysos, Markos Georgopoulos, Volkan Cevher

The Curse of Diversity in Ensemble-Based Exploration

Zhixuan Lin, Pierluca D'Oro, Evgenii Nikishin, Aaron Courville

Memorization in Self-Supervised Learning Improves Downstream Generalization

Wenhao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic, Michael Backes, Nicolas Papernot

PAC Prediction Sets Under Label Shift

Wenwen Si, Sangdon Park, Insup Lee, Edgar Dobriban, Osbert Bastani

Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control

Neehal Tumma, Mathias Lechner, Noel Loo, Ramin Hasani, Daniela Rus

Unbiased Watermark for Large Language Models

Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang

On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters

Matthias Lanzinger, Pablo Barceló

MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Sirui Hong, Mingchen Zhuge, Jonathan Chen, Xiawu Zheng, Yuheng Cheng

Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity

Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini

An improved analysis of per-sample and per-update clipping in federated learning

Bo Li, Xiaowen Jiang, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Sebastian U Stich

Symmetric Single Index Learning

Aaron Zweig, Joan Bruna

Hybrid Sharing for Multi-Label Image Classification

Zihao Yin, Chen Gan, Kelei He, Yang Gao, Junfeng Zhang

General Stability Analysis for Zeroth-Order Optimization Algorithms

Xinyue Liu, Hualin Zhang, Bin Gu, Hong Chen

Diving Segmentation Model into Pixels

Chen Gan, Zihao Yin, Kelei He, Yang Gao, Junfeng Zhang

On Adversarial Training without Perturbing all Examples

Max Losch, Mohamed Omran, David Stutz, Mario Fritz, Bernt Schiele

Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models

Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola

Hybrid Directional Graph Neural Network for Molecules

Junyi An, Chao Qu, Zhipeng Zhou, Fenglei Cao, Xu Yinghui

StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning

Shengzhong Zhang, Wenjie Yang, Xinyuan Cao, Hongwei Zhang, zengfeng Huang

TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks

Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi, Bin Gu, Huan Xiong

Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior

Kai Cui, Sascha H. Hauck, Christian Fabian, Heinz Koeppl

Maximum Entropy Heterogeneous-Agent Reinforcement Learning

Jiarong Liu, Yifan Zhong, Siyi Hu, Haobo Fu, Qiang Fu

Rethinking the Uniformity Metric in Self-Supervised Learning

Xianghong Fang, Jian Li, Qiang Sun, Benyou Wang

Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization

Hancheng Min, Enrique Mallada, René Vidal

Neural Architecture Retrieval

Xiaohuan Pei, Yanxi Li, Minjing Dong, Chang Xu

Removing Biases from Molecular Representations via Information Maximization

Chenyu Wang, Sharut Gupta, Caroline Uhler, Tommi S. Jaakkola

Incentive-Aware Federated Learning with Training-Time Model Rewards

Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar, Bryan Kian Hsiang Low

Gradual Domain Adaptation via Gradient Flow

Zhan Zhuang, Yu Zhang, Ying Wei

Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction

Ziyang Yu, Wenbing Huang, Yang Liu

Faster Approximation of Probabilistic and Distributional Values via Least Squares

Weida Li, Yaoliang Yu

Distinguished In Uniform: Self-Attention Vs. Virtual Nodes

Eran Rosenbluth, Jan Tönshoff, Martin Ritzert, Berke Kisin, Martin Grohe

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness

Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov, Ali Kavis, Kimon Antonakopoulos

Quantifying and Enhancing Multi-modal Robustness with Modality Preference

Zequn Yang, Yake Wei, Ce Liang, Di Hu

GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks

Renat Sergazinov, Elizabeth Chun, Valeriya Rogovchenko, Nathaniel J Fernandes, Nicholas Kasman

Masks, Signs, And Learning Rate Rewinding

Advait Harshal Gadhikar, Rebekka Burkholz

TextField3D: Towards Enhancing Open-Vocabulary 3D Generation with Noisy Text Fields

Tianyu Huang, Yihan Zeng, Bowen Dong, Hang Xu, Songcen Xu

Fine-Tuned Language Models Generate Stable Inorganic Materials as Text

Nate Gruver, Anuroop Sriram, Andrea Madotto, Andrew Gordon Wilson, C. Lawrence Zitnick

Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning

Li Ren, Chen Chen, Liqiang Wang, Kien A. Hua

Zipformer: A faster and better encoder for automatic speech recognition

Zengwei Yao, Liyong Guo, Xiaoyu Yang, Wei Kang, Fangjun Kuang

Energy-guided Entropic Neural Optimal Transport

Petr Mokrov, Alexander Korotin, Alexander Kolesov, Nikita Gushchin, Evgeny Burnaev

Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning

Finn Rietz, Erik Schaffernicht, Stefan Heinrich, Johannes A. Stork

Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control

Wenhan Cao, Wei Pan

DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines

Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam

Linear Log-Normal Attention with Unbiased Concentration

Yury Nahshan, Joseph Kampeas, Emir Haleva

Brain decoding: toward real-time reconstruction of visual perception

Yohann Benchetrit, Hubert Banville, Jean-Remi King

Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning

Haobo SONG, Hao Zhao, Soumajit Majumder, Tao LIN

Leave-one-out Distinguishability in Machine Learning

Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou, Reza Shokri

Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding

Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz

Near-Optimal Solutions of Constrained Learning Problems

Juan Elenter, Luiz F. O. Chamon, Alejandro Ribeiro

On the Reliability of Watermarks for Large Language Models

John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah

Chain-of-Experts: When LLMs Meet Complex Operations Research Problems

Ziyang Xiao, Dongxiang Zhang, Yangjun Wu, Lilin Xu, Yuan Jessica Wang

Weakly Supervised Virus Capsid Detection with Image-Level Annotations in Electron Microscopy Images

Hannah Kniesel, Leon Sick, Tristan Payer, Tim Bergner, Kavitha Shaga Devan

Convolutional Deep Kernel Machines

Edward Milsom, Ben Anson, Laurence Aitchison

Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation

Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection

Stefano B. Blumberg, Paddy J. Slator, Daniel C. Alexander

SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Saleh Ashkboos, Maximilian L. Croci, Marcelo Gennari do Nascimento, Torsten Hoefler, James Hensman

Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods

Sara Klein, Simon Weissmann, Leif Döring

Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis

Jie Hao, Xiaochuan Gong, Mingrui Liu

T-Rep: Representation Learning for Time Series using Time-Embeddings

Archibald Felix Fraikin, Adrien Bennetot, Stéphanie ALLASSONNIERE

DORSal: Diffusion for Object-centric Representations of Scenes et al.

Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom, Mehdi S. M. Sajjadi, Thomas Kipf

Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization

Amirhossein Vahidi, Simon Schosser, Lisa Wimmer, Yawei Li, Bernd Bischl

DyST: Towards Dynamic Neural Scene Representations on Real-World Videos

Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi

GAIA: Zero-shot Talking Avatar Generation

Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu

CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images

Olga Fourkioti, Matt De Vries, Chris Bakal

Understanding the Effects of RLHF on LLM Generalisation and Diversity

Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, Jelena Luketina, Eric Hambro

RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies

Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun

Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate

Miao Lu, Beining Wu, Xiaodong Yang, Difan Zou

Vision-by-Language for Training-Free Compositional Image Retrieval

Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata

Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation

Hongtao Wu, Ya Jing, Chilam Cheang, Guangzeng Chen, Jiafeng Xu

Clifford Group Equivariant Simplicial Message Passing Networks

Cong Liu, David Ruhe, Floor Eijkelboom, Patrick Forré

Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D

Haojie Huang, Owen Lewis Howell, Dian Wang, Xupeng Zhu, Robert Platt

Federated Wasserstein Distance

Alain Rakotomamonjy, Kimia Nadjahi, Liva Ralaivola

On Trajectory Augmentations for Off-Policy Evaluation

Ge Gao, Qitong Gao, Xi Yang, Song Ju, Miroslav Pajic

Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization

Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu, Aaron Courville, Yoshua Bengio

Large-scale Training of Foundation Models for Wearable Biosignals

Salar Abbaspourazad, Oussama Elachqar, Andrew Miller, Saba Emrani, Udhyakumar Nallasamy

Incentivized Truthful Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Tianze Ren, Haifeng Xu, Hongning Wang

The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.

Aaron Spieler, Nasim Rahaman, Georg Martius, Bernhard Schölkopf, Anna Levina

Training Socially Aligned Language Models on Simulated Social Interactions

Ruibo Liu, Ruixin Yang, Chenyan Jia, Ge Zhang, Diyi Yang

Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation

Konstantin Hess, Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel

BENO: Boundary-embedded Neural Operators for Elliptic PDEs

Haixin Wang, Jiaxin Li, Anubhav Dwivedi, Kentaro Hara, Tailin Wu

A Plug-and-Play Image Registration Network

Junhao Hu, Weijie Gan, Zhixin Sun, Hongyu An, Ulugbek Kamilov