ICLR 2024

2,260 papers

Looped Transformers are Better at Learning Learning Algorithms

Liu Yang, Kangwook Lee, Robert D Nowak, Dimitris Papailiopoulos

Whittle Index with Multiple Actions and State Constraint for Inventory Management

Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang

MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation

Min Zhang, Haoxuan Li, Fei Wu, Kun Kuang

Demystifying CLIP Data

Hu Xu, Saining Xie, Xiaoqing Tan, Po-Yao Huang, Russell Howes

SafeDreamer: Safe Reinforcement Learning with World Models

Weidong Huang, Jiaming Ji, Chunhe Xia, Borong Zhang, Yaodong Yang

PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback

Souradip Chakraborty, Amrit Bedi, Alec Koppel, Huazheng Wang, Dinesh Manocha

CAS: A Probability-Based Approach for Universal Condition Alignment Score

Chunsan Hong, ByungHee Cha, Tae-Hyun Oh

Backdoor Contrastive Learning via Bi-level Trigger Optimization

Weiyu Sun, Xinyu Zhang, Hao Lu, Ying-Cong Chen, Ting Wang

How to Fine-Tune Vision Models with SGD

Ananya Kumar, Ruoqi Shen, Sébastien Bubeck, Suriya Gunasekar

Evaluating Large Language Models at Evaluating Instruction Following

Zhiyuan Zeng, Jiatong Yu, Tianyu Gao, Yu Meng, Tanya Goyal

Contextual Bandits with Online Neural Regression

Rohan Deb, Yikun Ban, Shiliang Zuo, Jingrui He, Arindam Banerjee

Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification

Aditya Chattopadhyay, Kwan Ho Ryan Chan, René Vidal

Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents

Yang Deng, Wenxuan Zhang, Wai Lam, See-Kiong Ng, Tat-Seng Chua

Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning

Binwu Wang, Pengkun Wang, Wei Xu, Xu Wang, Yudong Zhang

In defense of parameter sharing for model-compression

Aditya Desai, Anshumali Shrivastava

Towards Understanding Factual Knowledge of Large Language Models

Xuming Hu, Junzhe Chen, Xiaochuan Li, Yufei Guo, Lijie Wen

Beating Price of Anarchy and Gradient Descent without Regret in Potential Games

Iosif Sakos, Stefanos Leonardos, Stelios Andrew Stavroulakis, William Overman, Ioannis Panageas

Understanding Addition in Transformers

Philip Quirke, Fazl Barez

Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes

Thiziri Nait Saada, Alireza Naderi, Jared Tanner

Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains

Wu Ran, Peirong Ma, Zhiquan He, Hao Ren, Hong Lu

Differentially Private Synthetic Data via Foundation Model APIs 1: Images

Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin

Image Background Serves as Good Proxy for Out-of-distribution Data

Sen Pei

AgentBench: Evaluating LLMs as Agents

Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei

Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning

Feiyang YE, Yueming LYU, Xuehao Wang, Yu Zhang, Ivor Tsang

Training Graph Transformers via Curriculum-Enhanced Attention Distillation

Yisong Huang, Jin Li, Xinlong Chen, Yang-Geng Fu

Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models

Shuai Fu, Xiequn Wang, Qiushi Huang, Yu Zhang

Identifying Policy Gradient Subspaces

Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel Haeufle

Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning

Pratik Patil, Daniel LeJeune

Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

Robin van de Water, Hendrik Nils Aurel Schmidt, Paul Elbers, Patrick Thoral, Bert Arnrich

Controlling Vision-Language Models for Multi-Task Image Restoration

Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön

Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models

Shaofei Shen, Chenhao Zhang, Yawen Zhao, Alina Bialkowski, Weitong Tony Chen

VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation

Jinxi Xiang, Ricong Huang, Jun Zhang, Guanbin Li, Xiao Han

Analyzing Feed-Forward Blocks in Transformers through the Lens of Attention Maps

Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi, Kentaro Inui

Making Retrieval-Augmented Language Models Robust to Irrelevant Context

Ori Yoran, Tomer Wolfson, Ori Ram, Jonathan Berant

On the Role of General Function Approximation in Offline Reinforcement Learning

Chenjie Mao, Qiaosheng Zhang, Zhen Wang, Xuelong Li

Evaluating Language Model Agency Through Negotiations

Tim Ruben Davidson, Veniamin Veselovsky, Michal Kosinski, Robert West

Some Fundamental Aspects about Lipschitz Continuity of Neural Networks

Grigory Khromov, Sidak Pal Singh

BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics

Suresh Bishnoi, Jayadeva Jayadeva, Sayan Ranu, N M Anoop Krishnan

Efficient Continual Finite-Sum Minimization

Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Tadesse Dadi, Volkan Cevher

Attention-based Iterative Decomposition for Tensor Product Representation

Taewon Park, Inchul Choi, Minho Lee

Querying Easily Flip-flopped Samples for Deep Active Learning

Seong Jin Cho, Gwangsu Kim, Junghyun Lee, Jinwoo Shin, Chang D. Yoo

ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs

Yogesh Verma, Markus Heinonen, Vikas Garg

Prometheus: Inducing Fine-Grained Evaluation Capability in Language Models

Seungone Kim, Jamin Shin, Yejin Cho, Joel Jang, Shayne Longpre

One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention

Arvind V. Mahankali, Tatsunori Hashimoto, Tengyu Ma

Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models

Fei Shen, Hu Ye, Jun Zhang, Cong Wang, Xiao Han

PAE: Reinforcement Learning from External Knowledge for Efficient Exploration

Zhe Wu, Haofei Lu, Junliang Xing, You Wu, Renye Yan

Deep Orthogonal Hypersphere Compression for Anomaly Detection

Yunhe Zhang, Yan Sun, Jinyu Cai, Jicong Fan

Learning Personalized Causally Invariant Representations for Heterogeneous Federated Clients

Xueyang Tang, Song Guo, Jie Zhang, Jingcai Guo

ED-NeRF: Efficient Text-Guided Editing of 3D Scene With Latent Space NeRF

Jangho Park, Gihyun Kwon, Jong Chul Ye

Topic Modeling as Multi-Objective Contrastive Optimization

Thong Thanh Nguyen, Xiaobao Wu, Xinshuai Dong, Cong-Duy T Nguyen, See-Kiong Ng

Kernelised Normalising Flows

Eshant English, Matthias Kirchler, Christoph Lippert

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling

Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang

Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation

Zhilong Zhang, Yihao Sun, Junyin Ye, Tian-Shuo Liu, Jiaji Zhang

Unlocking the Power of Representations in Long-term Novelty-based Exploration

Alaa Saade, Steven Kapturowski, Daniele Calandriello, Charles Blundell, Pablo Sprechmann

Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning

Yeda Song, Dongwook Lee, Gunhee Kim

H-GAP: Humanoid Control with a Generalist Planner

zhengyao jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner

CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs

Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer

Zero Bubble (Almost) Pipeline Parallelism

Penghui Qi, Xinyi Wan, Guangxing Huang, Min Lin

Exploring Weight Balancing on Long-Tailed Recognition Problem

Naoya Hasegawa, Issei Sato

Blending Imitation and Reinforcement Learning for Robust Policy Improvement

Xuefeng Liu, Takuma Yoneda, Rick Stevens, Matthew Walter, Yuxin Chen

ASMR: Activation-Sharing Multi-Resolution Coordinate Networks for Efficient Inference

Jason Chun Lok Li, Steven Tin Sui Luo, Le Xu, Ngai Wong

Do Generated Data Always Help Contrastive Learning?

Yifei Wang, Jizhe Zhang, Yisen Wang

Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model

Yinan Zheng, Jianxiong Li, Dongjie Yu, Yujie Yang, Shengbo Eben Li

Identifying Representations for Intervention Extrapolation

Sorawit Saengkyongam, Elan Rosenfeld, Pradeep Kumar Ravikumar, Niklas Pfister, Jonas Peters

Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing

Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee

Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks

Nguyen Hung-Quang, Yingjie Lao, Tung Pham, Kok-Seng Wong, Khoa D Doan

Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning

Hyungho Na, Yunkyeong Seo, Il-chul Moon

CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity

Aditya Bhatt, Daniel Palenicek, Boris Belousov, Max Argus, Artemij Amiranashvili

GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction

Oscar Sainz, Iker García-Ferrero, Rodrigo Agerri, Oier Lopez de Lacalle, German Rigau

Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design

Heng Dong, Junyu Zhang, Chongjie Zhang

Benchmarking Algorithms for Federated Domain Generalization

Ruqi Bai, Saurabh Bagchi, David I. Inouye

CircuitNet 2.0: An Advanced Dataset for Promoting Machine Learning Innovations in Realistic Chip Design Environment

Xun Jiang, zhuomin chai, Yuxiang Zhao, Yibo Lin, Runsheng Wang

Frequency-Aware Transformer for Learned Image Compression

Han Li, Shaohui Li, Wenrui Dai, Chenglin Li, Junni Zou

Safe RLHF: Safe Reinforcement Learning from Human Feedback

Josef Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu

Reward Model Ensembles Help Mitigate Overoptimization

Thomas Coste, Usman Anwar, Robert Kirk, David Krueger

CABINET: Content Relevance-based Noise Reduction for Table Question Answering

Sohan Patnaik, Heril Changwal, Milan Aggarwal, Sumit Bhatia, Yaman Kumar

Denoising Task Routing for Diffusion Models

Byeongjun Park, Sangmin Woo, Hyojun Go, Jin-Young Kim, Changick Kim

DOS: Diverse Outlier Sampling for Out-of-Distribution Detection

Wenyu Jiang, Hao Cheng, Mingcai Chen, Chongjun Wang, Hongxin Wei

Multi-View Causal Representation Learning with Partial Observability

Dingling Yao, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian

Global Optimality for Non-linear Constrained Restoration Problems via Invexity

Samuel Pinilla, Jeyan Thiyagalingam

Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?

Jianfei Yang, Hanjie Qian, Yuecong Xu, Kai Wang, Lihua Xie

LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation

Suhyeon Lee, Won Jun Kim, Jinho Chang, Jong Chul Ye

Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data

Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang

Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation

Tuan Le, Julian Cremer, Frank Noe, Djork-Arné Clevert, Kristof T Schütt

Hindsight PRIORs for Reward Learning from Human Preferences

Mudit Verma, Katherine Metcalf

Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution

Shanqi Liu, Dong Xing, Pengjie Gu, Xinrun Wang, Bo An

Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training

Shruthi Gowda, Bahram Zonooz, Elahe Arani

Traveling Waves Encode The Recent Past and Enhance Sequence Learning

T. Anderson Keller, Lyle Muller, Terrence Sejnowski, Max Welling

Mitigating Emergent Robustness Degradation while Scaling Graph Learning

Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang

InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists

Yulu Gan, Sungwoo Park, Alexander Marcel Schubert, Anthony Philippakis, Ahmed Alaa

Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning

Haowen Wang, Tao Sun, Congyun Jin, Yingbo Wang, Yibo Fan

FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling

Yu Tian, Min Shi, Yan Luo, Ava Kouhana, Tobias Elze

Logical Languages Accepted by Transformer Encoders with Hard Attention

Pablo Barceló, Alexander Kozachinskiy, Anthony Widjaja Lin, Vladimir Podolskii

GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations

zaishuo xia, Han Yang, Binghui Wang, Jinyuan Jia

Implicit Gaussian process representation of vector fields over arbitrary latent manifolds

Robert Peach, Matteo Vinao-Carl, Nir Grossman, Michael David, Emma Mallas

CLEX: Continuous Length Extrapolation for Large Language Models

Guanzheng Chen, Xin Li, Zaiqiao Meng, Shangsong Liang, Lidong Bing

EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models

Koichi Namekata, Amirmojtaba Sabour, Sanja Fidler, Seung Wook Kim

Graph Neural Networks for Learning Equivariant Representations of Neural Networks

Miltiadis Kofinas, Boris Knyazev, Yan Zhang, Yunlu Chen, Gertjan J. Burghouts

Expressivity of ReLU-Networks under Convex Relaxations

Maximilian Baader, Mark Niklas Mueller, Yuhao Mao, Martin Vechev

Adversarial Feature Map Pruning for Backdoor

Dong Huang, Qingwen Bu