ICLR 2024

2,260 papers

Efficient ConvBN Blocks for Transfer Learning and Beyond

Kaichao You, Guo Qin, Anchang Bao, Meng Cao, Ping Huang

Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment

Bowen Gao, Yinjun Jia, YuanLe Mo, Yuyan Ni, Wei-Ying Ma

Language Model Decoding as Direct Metrics Optimization

Haozhe Ji, Pei Ke, Hongning Wang, Minlie Huang

Hypothesis Search: Inductive Reasoning with Language Models

Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber

Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs

Lean Wang, Wenkai Yang, Deli Chen, Hao Zhou, Yankai Lin

Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms

Ge Yan, Hongxu Chen, Kaisen Pan, Junchi Yan

Self-Supervised Dataset Distillation for Transfer Learning

Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee

Coordinate-Aware Modulation for Neural Fields

Joo Chan Lee, Daniel Rho, Seungtae Nam, Jong Hwan Ko, Eunbyung Park

At Which Training Stage Does Code Data Help LLMs Reasoning?

Yingwei Ma, Yue Liu, Yue Yu, Yuanliang Zhang, Yu Jiang

Minimum width for universal approximation using ReLU networks on compact domain

Namjun Kim, Chanho Min, Sejun Park

Sample-Efficient Multi-Agent RL: An Optimization Perspective

Nuoya Xiong, Zhihan Liu, Zhaoran Wang, Zhuoran Yang

Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models

Hritik Bansal, John Dang, Aditya Grover

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer

Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka

Object-Aware Inversion and Reassembly for Image Editing

Zhen Yang, Ganggui Ding, Wen Wang, Hao Chen, Bohan Zhuang

InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

Xingchao Liu, Xiwen Zhang, Jianzhu Ma, Jian Peng, Qiang Liu

A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error

Erdun Gao, Howard Bondell, Wei Huang, Mingming Gong

CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets

Lifan Yuan, Yangyi Chen, Xingyao Wang, Yi Fung, Hao Peng

PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images

Jinsung Jeon, Hyundong Jin, Jonghyun Choi, Sanghyun Hong, Dongeun Lee

DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

Licheng Wen, Daocheng Fu, Xin Li, Xinyu Cai, Tao Ma

Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models

Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre

LEGO-Prover: Neural Theorem Proving with Growing Libraries

Haiming Wang, Huajian Xin, Chuanyang Zheng, Zhengying Liu, Qingxing Cao

Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces

Fabian Akkerman, Julius Luy, Wouter van Heeswijk, Maximilian Schiffer

Efficient Backpropagation with Variance Controlled Adaptive Sampling

Ziteng Wang, Jianfei Chen, Jun Zhu

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization

Yang Jin, Kun Xu, Liwei Chen, Chao Liao, Jianchao Tan

AnyText: Multilingual Visual Text Generation and Editing

Yuxiang Tuo, Wangmeng Xiang, Jun-Yan He, Yifeng Geng, Xuansong Xie

NeRM: Learning Neural Representations for High-Framerate Human Motion Synthesis

Dong Wei, Huaijiang Sun, Bin Li, Xiaoning Sun, Shengxiang Hu

How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization

Nuoya Xiong, Lijun Ding, Simon Shaolei Du

EventRPG: Event Data Augmentation with Relevance Propagation Guidance

Mingyuan Sun, Donghao Zhang, Zongyuan Ge, WANG Jiaxu, Jia Li

Efficient Multi-agent Reinforcement Learning by Planning

Qihan Liu, Jianing Ye, Xiaoteng Ma, Jun Yang, Bin Liang

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization

Guowei Xu, Ruijie Zheng, Yongyuan Liang, Xiyao Wang, Zhecheng Yuan

Learning Multi-Agent Communication from Graph Modeling Perspective

Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao

Space Group Constrained Crystal Generation

Rui Jiao, Wenbing Huang, Yu Liu, Deli Zhao, Yang Liu

Towards Faithful XAI Evaluation via Generalization-Limited Backdoor Watermark

Mengxi Ya, Yiming Li, Tao Dai, Bin Wang, Yong Jiang

ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models

Yingqing He, Shaoshu Yang, Haoxin Chen, Xiaodong Cun, Menghan Xia

Reinforcement Symbolic Regression Machine

Yilong Xu, Yang Liu, Hao Sun

CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting

xue wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding

DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation

Yukun Huang, Jianan Wang, Yukai Shi, Boshi Tang, Xianbiao Qi

TokenFlow: Consistent Diffusion Features for Consistent Video Editing

Michal Geyer, Omer Bar-Tal, Shai Bagon, Tali Dekel

Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning

Juan Rocamonde, Victoriano Montesinos, Elvis Nava, Ethan Perez, David Lindner

Fast Updating Truncated SVD for Representation Learning with Sparse Matrices

Haoran Deng, Yang Yang, Jiahe Li, Cheng Chen, Weihao Jiang

Improving the Convergence of Dynamic NeRFs via Optimal Transport

Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham, Hisham Husain, Anton van den Hengel

Multi-Source Diffusion Models for Simultaneous Music Generation and Separation

Giorgio Mariani, Irene Tallini, Emilian Postolache, Michele Mancusi, Luca Cosmo

Relay Diffusion: Unifying diffusion process across resolutions for image synthesis

Jiayan Teng, Wendi Zheng, Ming Ding, Wenyi Hong, Jianqiao Wangni

Addressing Signal Delay in Deep Reinforcement Learning

Wei Wang, Dongqi Han, Xufang Luo, Dongsheng Li

Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback

Yifu Yuan, Jianye Hao, Yi Ma, Zibin Dong, Hebin Liang

HoloNets: Spectral Convolutions do extend to Directed Graphs

Christian Koke, Daniel Cremers

Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning

HeeSun Bae, Seungjae Shin, Byeonghu Na, Il-chul Moon

Emu: Generative Pretraining in Multimodality

Quan Sun, Qiying Yu, Yufeng Cui, Fan Zhang, Xiaosong Zhang

Augmented Bayesian Policy Search

Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo

Hypergraph Dynamic System

Jielong Yan, Yifan Feng, Shihui Ying, Yue Gao

SweetDreamer: Aligning Geometric Priors in 2D diffusion for Consistent Text-to-3D

Weiyu Li, Rui Chen, Xuelin Chen, Ping Tan

Exploring Diffusion Time-steps for Unsupervised Representation Learning

Zhongqi Yue, Jiankun Wang, Qianru Sun, Lei Ji, Eric I-Chao Chang

Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition

Sangyu Han, Yearim Kim, Nojun Kwak

Select to Perfect: Imitating desired behavior from large multi-agent data

Tim Franzmeyer, Edith Elkind, Philip Torr, Jakob Nicolaus Foerster, João F. Henriques

Illusory Attacks: Information-theoretic detectability matters in adversarial attacks

Tim Franzmeyer, Stephen Marcus McAleer, João F. Henriques, Jakob Nicolaus Foerster, Philip Torr

FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation

Haozhao Wang, Haoran Xu, Yichen Li, Yuan Xu, Ruixuan Li

ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion

Shangyu Wu, Ying Xiong, Yufei CUI, Xue Liu, Buzhou Tang

SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation

Qianxu Wang, Haotong Zhang, Congyue Deng, Yang You, Hao Dong

DeepSPF: Spherical SO(3)-Equivariant Patches for Scan-to-CAD Estimation

Driton Salihu, Adam Misik, Yuankai Wu, Constantin Patsch, Fabian Seguel

Idempotent Generative Network

Assaf Shocher, Amil V Dravid, Yossi Gandelsman, Inbar Mosseri, Michael Rubinstein

Learning to solve Class-Constrained Bin Packing Problems via Encoder-Decoder Model

Hanni Cheng, Ya Cong, Weihao Jiang, Shiliang Pu

Unveiling and Manipulating Prompt Influence in Large Language Models

Zijian Feng, Hanzhang Zhou, Zixiao Zhu, Junlang Qian, Kezhi Mao

Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning

Geraud Nangue Tasse, Devon Jarvis, Steven James, Benjamin Rosman

A Neural Framework for Generalized Causal Sensitivity Analysis

Dennis Frauen, Fergus Imrie, Alicia Curth, Valentyn Melnychuk, Stefan Feuerriegel

From Posterior Sampling to Meaningful Diversity in Image Restoration

Noa Cohen, Hila Manor, Yuval Bahat, Tomer Michaeli

DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks

Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang

FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning

Mingkun Yang, Ran Zhu, Qing Wang, jie Yang

SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem

Margalit Glasgow

Knowledge Fusion of Large Language Models

Fanqi Wan, Xinting Huang, Deng Cai, Xiaojun Quan, Wei Bi

Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization

Ian Gemp, Luke Marris, Georgios Piliouras

Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression

Ivan Butakov, Alexander Tolmachev, Sofia Malanchuk, Anna Neopryatnaya, Alexey Frolov

RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering

Kai-Po Chang, Chi-Pin Huang, Wei-Yuan Cheng, Fu-En Yang, Chien-Yi Wang

Learning Energy Decompositions for Partial Inference in GFlowNets

Hyosoon Jang, Minsu Kim, Sungsoo Ahn

Successor Heads: Recurring, Interpretable Attention Heads In The Wild

Rhys Gould, Euan Ong, George Ogden, Arthur Conmy

MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy

Yan Sun, Jicong Fan

JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling

Jingyang Zhang, Shiwei Li, Yuanxun Lu, Tian Fang, David Neil McKinnon

An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment

Sergei Solonets, Daniil Sinitsyn, Lukas von Stumberg, Nikita Araslanov, Daniel Cremers

Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG

Jonas Seng, Matej Zečević, Devendra Singh Dhami, Kristian Kersting

Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space

Erik J Bekkers, Sharvaree Vadgama, Rob Hesselink, Putri A Van der Linden, David W. Romero

Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise

Rui Pan, Yuxing Liu, Xiaoyu Wang, Tong Zhang

Elucidating the Exposure Bias in Diffusion Models

Mang Ning, Mingxiao Li, Jianlin Su, Albert Ali Salah, Itir Onal Ertugrul

Grokking as a First Order Phase Transition in Two Layer Networks

Noa Rubin, Inbar Seroussi, Zohar Ringel

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation

Xinyu Tang, Richard Shin, Huseyin A Inan, Andre Manoel, FatemehSadat Mireshghallah

A Mutual Information Perspective on Federated Contrastive Learning

Christos Louizos, Matthias Reisser, Denis Korzhenkov

TOSS: High-quality Text-guided Novel View Synthesis from a Single Image

Yukai Shi, Jianan Wang, He CAO, Boshi Tang, Xianbiao Qi

Inherently Interpretable Time Series Classification via Multiple Instance Learning

Joseph Early, Gavin Cheung, Kurt Cutajar, Hanting Xie, Jas Kandola

Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm

Wei Yao, Chengming Yu, Shangzhi Zeng, Jin Zhang

FedInverse: Evaluating Privacy Leakage in Federated Learning

Di Wu, Jun Bai, Yiliao Song, Junjun Chen, Wei Zhou

The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning

Tian Jin, Nolan Clement, Xin Dong, Vaishnavh Nagarajan, Michael Carbin

AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation

Zihao Tang, Zheqi Lv, Shengyu Zhang, Yifan Zhou, Xinyu Duan

True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning

Weihao Tan, Wentao Zhang, Shanqi Liu, Longtao Zheng, Xinrun Wang

A Simple and Scalable Representation for Graph Generation

Yunhui Jang, Seul Lee, Sungsoo Ahn

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem

Simon Segert

Enhancing Neural Training via a Correlated Dynamics Model

Jonathan Brokman, Roy Betser, Rotem Turjeman, Tom Berkov, Ido Cohen

Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs

Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu

Entity-Centric Reinforcement Learning for Object Manipulation from Pixels

Dan Haramati, Tal Daniel, Aviv Tamar

Unknown Domain Inconsistency Minimization for Domain Generalization

Seungjae Shin, HeeSun Bae, Byeonghu Na, Yoon-Yeong Kim, Il-chul Moon

On the Limitations of Temperature Scaling for Distributions with Overlaps

Muthu Chidambaram, Rong Ge

Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation

Shahar Lutati, Eliya Nachmani, Lior Wolf

Fixed-Budget Differentially Private Best Arm Identification

Zhirui Chen, P. N. Karthik, Yeow Meng Chee, Vincent Tan