ICLR 2024

2,260 papers

Batched Low-Rank Adaptation of Foundation Models

Yeming Wen, Swarat Chaudhuri

Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization

Yinbin Han, Meisam Razaviyayn, Renyuan Xu

Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning

Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum

Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning

Zihan Ding, Chi Jin

ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis

Kensen Shi, Joey Hong, Yinlin Deng, Pengcheng Yin, Manzil Zaheer

DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow

Kyungmin Lee, Kihyuk Sohn, Jinwoo Shin

Protein Discovery with Discrete Walk-Jump Sampling

Nathan C. Frey, Dan Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse

Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models

Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh

CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding

Qiongyi Zhou, Changde Du, Shengpei Wang, Huiguang He

LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors

Sheng Jin, Xueying Jiang, Jiaxing Huang, Lewei Lu, Shijian Lu

WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions

Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao

Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning

Sheng Li, Chao Wu, Ao Li, Yanzhi Wang, Xulong Tang

Learning Hierarchical Image Segmentation For Recognition and By Recognition

Tsung-Wei Ke, Sangwoo Mo, Stella X. Yu

WildChat: 1M ChatGPT Interaction Logs in the Wild

Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi

Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks

Hao Chen, Jindong Wang, Ankit Shah, Ran Tao, Hongxin Wei

Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration

Yujia Wang, Yuanpu Cao, Jingcheng Wu, Ruoyu Chen, Jinghui Chen

Steve-Eye: Equipping LLM-based Embodied Agents with Visual Perception in Open Worlds

Sipeng Zheng, Jiazheng Liu, Yicheng Feng, Zongqing Lu

Online GNN Evaluation Under Test-time Graph Distribution Shifts

Xin Zheng, Dongjin Song, Qingsong Wen, Bo Du, Shirui Pan

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization

Yidong Wang, Zhuohao Yu, Wenjin Yao, Zhengran Zeng, Linyi Yang

Communication-Efficient Federated Non-Linear Bandit Optimization

Chuanhao Li, Chong Liu, Yu-Xiang Wang

DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption

Nan Yin, Mengzhu Wang, Zhenghan Chen, Li Shen, Huan Xiong

Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints

Jian Chen, Ruiyi Zhang, Yufan Zhou, Changyou Chen

Demystifying Linear MDPs and Novel Dynamics Aggregation Framework

Joongkyu Lee, Min-hwan Oh

Treatment Effects Estimation By Uniform Transformer

Ruoqi Yu, Shulei Wang

CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding

Junyan Li, Delin Chen, Yining Hong, Zhenfang Chen, Peihao Chen

Deep Temporal Graph Clustering

Meng Liu, Yue Liu, Ke Liang, Wenxuan Tu, Siwei Wang

LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning

Han Guo, Philip Greengard, Eric Xing, Yoon Kim

Spectrally Transformed Kernel Regression

Runtian Zhai, Rattana Pukdee, Roger Jin, Maria Florina Balcan, Pradeep Kumar Ravikumar

Proper Laplacian Representation Learning

Diego Gomez, Michael Bowling, Marlos C. Machado

A Sublinear Adversarial Training Algorithm

Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases

Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao

Language Model Beats Diffusion - Tokenizer is key to visual generation

Lijun Yu, José Lezama, Nitesh Bharadwaj Gundavarapu, Luca Versari, Kihyuk Sohn

Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation

Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang

Deep Confident Steps to New Pockets: Strategies for Docking Generalization

Gabriele Corso, Arthur Deng, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola

The Human-AI Substitution game: active learning from a strategic labeler

Tom Yan, Chicheng Zhang

GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs

Pengcheng Jiang, Cao Xiao, Adam Richard Cross, Jimeng Sun

D^2 Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning

Adyasha Maharana, Prateek Yadav, Mohit Bansal

BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference

Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng

MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li

A unique M-pattern for micro-expression spotting in long videos

Jinxuan Wang, Shiting Xu, Tong Zhang

Pre-training Sequence, Structure, and Surface Features for Comprehensive Protein Representation Learning

YouHan Lee, Hasun Yu, Jaemyung Lee, Jaehoon Kim

Learning Grounded Action Abstractions from Language

Lionel Wong, Jiayuan Mao, Pratyusha Sharma, Zachary S Siegel, Jiahai Feng

On Bias-Variance Alignment in Deep Models

Lin Chen, MICHAL LUKASIK, Wittawat Jitkrittum, Chong You, Sanjiv Kumar

Learning Hierarchical Polynomials with Three-Layer Neural Networks

Zihao Wang, Eshaan Nichani, Jason D. Lee

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping

Yining Li, Peizhong Ju, Ness Shroff

Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation

Ziqi Wang, Chengpeng Hu, Jialin Liu, Xin Yao

Adaptive Regret for Bandits Made Possible: Two Queries Suffice

Zhou Lu, Qiuyi Zhang, Xinyi Chen, Fred Zhang, David Woodruff

Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy

Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng

Making RL with Preference-based Feedback Efficient via Randomization

Runzhe Wu, Wen Sun

Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness

Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He

Generating Pragmatic Examples to Train Neural Program Synthesizers

Saujas Vaduguru, Daniel Fried, Yewen Pu

Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs

Ilan Naiman, N. Benjamin Erichson, Pu Ren, Michael W. Mahoney, Omri Azencot

Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies

Xiangyu Liu, Chenghao Deng, Yanchao Sun, Yongyuan Liang, Furong Huang

Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance

Giung Nam, Byeongho Heo, Juho Lee

MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following

Renze Lou, Kai Zhang, jian xie, Yuxuan Sun, Janice Ahn

Concept Bottleneck Generative Models

Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo, Stephen Ra, Kyunghyun Cho

Robustifying and Boosting Training-Free Neural Architecture Search

Zhenfeng He, YAO SHU, Zhongxiang Dai, Bryan Kian Hsiang Low

Score Regularized Policy Optimization through Diffusion Behavior

Huayu Chen, Cheng Lu, Zhengyi Wang, Hang Su, Jun Zhu

Goodhart's Law in Reinforcement Learning

Jacek Karwowski, Oliver Hayman, Xingjian Bai, Klaus Kiendlhofer, Charlie Griffin

Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty

Changbin Li, Kangshuo Li, Yuzhe Ou, Lance M. Kaplan, Audun Jøsang

Grounding Language Plans in Demonstrations Through Counterfactual Perturbations

Yanwei Wang, Tsun-Hsuan Wang, Jiayuan Mao, Michael Hagenow, Julie Shah

Vanishing Gradients in Reinforcement Finetuning of Language Models

Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley

GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules

Zhenfang Chen, Rui Sun, Wenjun Liu, Yining Hong, Chuang Gan

COLLIE: Systematic Construction of Constrained Text Generation Tasks

Shunyu Yao, Howard Chen, Austin W. Hanjie, Runzhe Yang, Karthik R Narasimhan

Understanding Expressivity of GNN in Rule Learning

Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao

Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models

Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu

Christopher A. Choquette-Choo, Krishnamurthy Dj Dvijotham, Krishna Pillutla, Arun Ganesh, Thomas Steinke

Image Clustering Conditioned on Text Criteria

Sehyun Kwon, Jaeseung Park, Minkyu Kim, Jaewoong Cho, Ernest K. Ryu

Non-negative Contrastive Learning

Yifei Wang, Qi Zhang, Yaoyu Guo, Yisen Wang

Understanding Domain Generalization: A Noise Robustness Perspective

Rui Qiao, Bryan Kian Hsiang Low

DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models

Yongchan Kwon, Eric Wu, Kevin Wu, James Zou

Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization

Hamidreza Almasi, Harsh Mishra, Balajee Vamanan, Sathya N. Ravi

Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning

Xiongye Xiao, Gengshuo Liu, Gaurav Gupta, Defu Cao, Shixuan Li

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement

Linlu Qiu, Liwei Jiang, Ximing Lu, Melanie Sclar, Valentina Pyatkin

Training-free Multi-objective Diffusion Model for 3D Molecule Generation

Xu Han, Caihua Shan, Yifei Shen, Can Xu, Han Yang

Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders

Hien Dang, Tho Tran Huu, Tan Minh Nguyen, nhật Hồ

What Algorithms can Transformers Learn? A Study in Length Generalization

Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi

Ensemble Distillation for Unsupervised Constituency Parsing

Behzad Shayegh, Yanshuai Cao, Xiaodan Zhu, Jackie CK Cheung, Lili Mou

ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search

Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn

Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling

Hyungi Lee, Giung Nam, Edwin Fong, Juho Lee

Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback

Yu Chen, Yihan Du, Pihe Hu, Siwei Wang, Desheng Wu

The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models

Yan Liu, Yu Liu, Xiaokang Chen, Pin-Yu Chen, Daoguang Zan

Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts

Huy Nguyen, Pedram Akbarian, Fanqi Yan, nhật Hồ

Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models

Kyuyoung Kim, Jongheon Jeong, Minyong An, Mohammad Ghavamzadeh, Krishnamurthy Dj Dvijotham

Dynamic Neural Response Tuning

Tian Qiu, Wenxiang Xu, Lin Chen, Linyun Zhou, Zunlei Feng

On the Stability of Expressive Positional Encodings for Graphs

Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang

Spatially-Aware Transformers for Embodied Agents

Junmo Cho, Jaesik Yoon, Sungjin Ahn

Grounded Object-Centric Learning

Avinash Kori, Francesco Locatello, Fabio De Sousa Ribeiro, Francesca Toni, Ben Glocker

Adversarial AutoMixup

Huafeng Qin, Xin Jin, Yun Jiang, Mounîm El-Yacoubi, Xinbo Gao

Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space

Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin

GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking

Mert Kosan, Samidha Verma, Burouj Armgaan, Khushbu Pahwa, Ambuj Singh

Explaining Time Series via Contrastive and Locally Sparse Perturbations

Zichuan Liu, Yingying Zhang, Tianchun Wang, Zefan Wang, Dongsheng Luo

SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction

Xinyuan Chen, Yaohui Wang, Lingjun Zhang, Shaobin Zhuang, Xin Ma

Fake It Till Make It: Federated Learning with Consensus-Oriented Generation

Rui Ye, Yaxin Du, Zhenyang Ni, Yanfeng Wang, Siheng Chen

Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks

Bhaskar Mukhoty, Hilal AlQuabeh, Giulia De Masi, Huan Xiong, Bin Gu

Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication

June Yong Yang, Geondo Park, Joowon Kim, Hyeongwon Jang, Eunho Yang

Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?

Tokio Kajitsuka, Issei Sato

Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability

Ivan Lee, Nan Jiang, Taylor Berg-Kirkpatrick

Learning Thresholds with Latent Values and Censored Feedback

Jiahao Zhang, Tao LIN, Weiqiang Zheng, Zhe Feng, Yifeng Teng

Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs

Milan Papez, Martin Rektoris, Vaclav Smidl, Tomas Pevny