ICLR

Learning Galaxy Intrinsic Alignment Correlations

Sneh Pandya, Yuanyuan Yang, Nicholas Van Alfen, Jonathan Blazek, Robin Walters

Comments 15 pages, 6 figures, 1 table. Accepted at the Data-centric Machine Learning Research (DMLR) Workshop at ICLR 2024

Data-independent Module-aware Pruning for Hierarchical Vision Transformers

Yang He, Joey Tianyi Zhou

Comments Accepted by ICLR 2024

Accelerating the Generation of Molecular Conformations with Progressive Distillation of Equivariant Latent Diffusion Models

Romain Lacombe, Neal Vaidya

Comments Accepted at the Generative and Experimental Perspectives for Biomolecular Design Workshop at the 12th International Conference on Learning Representations, 2024

Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks

Ben Eisner, Yi Yang, Todor Davchev, Mel Vecerik, Jonathan Scholz, David Held

Comments Published at International Conference on Representation Learning (ICLR 2024)

DNA: Differentially private Neural Augmentation for contact tracing

Rob Romijnders, Christos Louizos, Yuki M. Asano, Max Welling

Comments Privacy Regulation and Protection in Machine Learning Workshop at ICLR 2024

SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs

Jaehyung Kim, Jaehyun Nam, Sangwoo Mo, Jongjin Park, Sang-Woo Lee, Minjoon Seo, Jung-Woo Ha, Jinwoo Shin

Comments Accepted at ICLR 2024

Bridging State and History Representations: Understanding Self-Predictive RL

Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon

Comments ICLR 2024 (Poster). Code is available at https://github.com/twni2016/self-predictive-rl

Unraveling the Key Components of OOD Generalization via Diversification

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

Comments ICLR 2024

Domain constraints improve risk prediction when outcome data is missing

Sidhika Balachandar, Nikhil Garg, Emma Pierson

Comments Published at ICLR 2024

Pre-training with Random Orthogonal Projection Image Modeling

Maryam Haghighat, Peyman Moghadam, Shaheer Mohamed, Piotr Koniusz

Comments Published as a conference paper at the International Conference on Learning Representations (ICLR) 2024. 19 pages

Think before you speak: Training Language Models With Pause Tokens

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

Comments Published at ICLR 2024

Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models

Ashutosh Baheti, Ximing Lu, Faeze Brahman, Ronan Le Bras, Maarten Sap, Mark Riedl

Comments published at ICLR 2024

Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization

Hanmin Li, Avetik Karagulyan, Peter Richtárik

Comments 9 pages, 39 figures, published in ICLR 2024

Towards Logically Consistent Language Models via Probabilistic Reasoning

Diego Calanzone, Stefano Teso, Antonio Vergari

Comments Accepted at ICLR 2024 Workshop on Reliable and Responsible Foundation Models

Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation

Jianliang He, Han Zhong, Zhuoran Yang

Comments ICLR 2024

Neural Active Learning Beyond Bandits

Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He

Comments Published on ICLR 2024, 40 Pages

AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval

Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, Tristan Sylvain

Comments ICLR 2024

Frequency-Aware Masked Autoencoders for Multimodal Pretraining on Biosignals

Ran Liu, Ellen L. Zippi, Hadi Pouransari, Chris Sandino, Jingping Nie, Hanlin Goh, Erdrin Azemi, Ali Moin

Comments Extended version of ICLR 2024 Learning from Time Series for Health workshop

Efficient Backdoor Attacks for Deep Neural Networks in Real-world Scenarios

Ziqiang Li, Hong Sun, Pengfei Xia, Heng Li, Beihao Xia, Yi Wu, Bin Li

Comments ICLR 2024

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

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

Comments 21 pages, 14 figures

Journal ref International Conference on Learning Representations 2024

Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs

Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Manish Singh, Toyotaro Suzumura

Comments Accepted as a full conference paper in the International Conference on Learning Representations 2024

Quantifying and Enhancing Multi-modal Robustness with Modality Preference

Zequn Yang, Yake Wei, Ce Liang, Di Hu

Comments Accepted to ICLR 2024

Explaining latent representations of generative models with large multimodal models

Mengdan Zhu, Zhenke Liu, Bo Pan, Abhinav Angirekula, Liang Zhao

Comments ICLR 2024 Workshop on Reliable and Responsible Foundation Models

Mobile-Agent: Autonomous Multi-Modal Mobile Device Agent with Visual Perception

Junyang Wang, Haiyang Xu, Jiabo Ye, Ming Yan, Weizhou Shen, Ji Zhang, Fei Huang, Jitao Sang

Comments Accepted by ICLR 2024 Workshop in Large Language Model (LLM) Agents

Generalized Schrödinger Bridge Matching

Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos A. Theodorou, Ricky T. Q. Chen

Comments ICLR 2024 Camera Ready

One-shot Empirical Privacy Estimation for Federated Learning

Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith M. Suriyakumar

Comments Final revision, oral presentation at ICLR 2024

Variational Bayesian Last Layers

James Harrison, John Willes, Jasper Snoek

Comments International Conference on Learning Representations (ICLR) 2024

Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty

Changbin Li, Kangshuo Li, Yuzhe Ou, Lance M. Kaplan, Audun Jøsang, Jin-Hee Cho, Dong Hyun Jeong, Feng Chen

Comments In Proceedings of The Twelfth International Conference on Learning Representations, ICLR 2024

Locality Sensitive Sparse Encoding for Learning World Models Online

Zichen Liu, Chao Du, Wee Sun Lee, Min Lin

Comments ICLR 2024

Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF

Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell

Comments Presented at ICLR 2024