ICLR

Identifying and interpreting non-aligned human conceptual representations using language modeling

Wanqian Bao, Uri Hasson

Comments To appear at the ICLR 2024 Workshop on Representational Alignment (Re-Align)

Democratizing Fine-grained Visual Recognition with Large Language Models

Mingxuan Liu, Subhankar Roy, Wenjing Li, Zhun Zhong, Nicu Sebe, Elisa Ricci

Comments Accepted as a conference paper at ICLR 2024; Project page: https://projfiner.github.io/

LRM: Large Reconstruction Model for Single Image to 3D

Yicong Hong, Kai Zhang, Jiuxiang Gu, Sai Bi, Yang Zhou, Difan Liu, Feng Liu, Kalyan Sunkavalli, Trung Bui, Hao Tan

Comments ICLR 2024

Towards Robust Offline Reinforcement Learning under Diverse Data Corruption

Rui Yang, Han Zhong, Jiawei Xu, Amy Zhang, Chongjie Zhang, Lei Han, Tong Zhang

Comments Accepted by ICLR 2024

METRA: Scalable Unsupervised RL with Metric-Aware Abstraction

Seohong Park, Oleh Rybkin, Sergey Levine

Comments ICLR 2024

Prometheus: Inducing Fine-grained Evaluation Capability in Language Models

Seungone Kim, Jamin Shin, Yejin Cho, Joel Jang, Shayne Longpre, Hwaran Lee, Sangdoo Yun, Seongjin Shin, Sungdong Kim, James Thorne, Minjoon Seo

Comments ICLR 2024

AutoVP: An Automated Visual Prompting Framework and Benchmark

Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu, Tsung-Yi Ho

Comments ICLR 2024

Reward Model Ensembles Help Mitigate Overoptimization

Thomas Coste, Usman Anwar, Robert Kirk, David Krueger

Comments Accepted at ICLR 2024

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

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

Comments Accepted by ICLR 2024

Large Language Models as Analogical Reasoners

Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou

Comments Published at ICLR 2024

Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects

Chunming He, Kai Li, Yachao Zhang, Yulun Zhang, Zhenhua Guo, Xiu Li, Martin Danelljan, Fisher Yu

Comments Accepted at ICLR 2024

Prediction Error-based Classification for Class-Incremental Learning

Michał Zając, Tinne Tuytelaars, Gido M. van de Ven

Comments ICLR 2024 camera ready

Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural Networks

Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Kang Liu, Jun Zhao

Comments Accepted in ICLR 2024

Poly-View Contrastive Learning

Amitis Shidani, Devon Hjelm, Jason Ramapuram, Russ Webb, Eeshan Gunesh Dhekane, Dan Busbridge

Comments Accepted to ICLR 2024. 42 pages, 7 figures, 3 tables, loss pseudo-code included in appendix

On Representing Electronic Wave Functions with Sign Equivariant Neural Networks

Nicholas Gao, Stephan Günnemann

Comments Published at Workshop on AI4DifferentialEquations in Science at ICLR 2024

VTruST: Controllable value function based subset selection for Data-Centric Trustworthy AI

Soumi Das, Shubhadip Nag, Shreyyash Sharma, Suparna Bhattacharya, Sourangshu Bhattacharya

Comments Accepted in ICLR 2024 DMLR workshop

On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods

Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji

Comments To appear at ICLR 2024 (Spotlight paper). 17 pages, 10 figures

Knowledge Distillation Based on Transformed Teacher Matching

Kaixiang Zheng, En-Hui Yang

Comments Published as a conference paper at ICLR 2024

FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data

Zikai Xiao, Zihan Chen, Liyinglan Liu, Yang Feng, Jian Wu, Wanlu Liu, Joey Tianyi Zhou, Howard Hao Yang, Zuozhu Liu

Comments Accepted by ICLR 2024, code: https://github.com/ZackZikaiXiao/FedLoGe

REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes

David Ireland, Giovanni Montana

Comments ICLR camera ready version

Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information

Linfeng Ye, Shayan Mohajer Hamidi, Renhao Tan, En-Hui Yang

Comments 32 pages, 19 figures, Published as a conference paper at ICLR 2024

Journal ref International Conference on Learning Representations 2024 (ICLR)

Balancing Act: Constraining Disparate Impact in Sparse Models

Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran, Golnoosh Farnadi, Simon Lacoste-Julien, Jose Gallego-Posada

Comments Published at ICLR 2024. Code available at https://github.com/merajhashemi/balancing-act

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models

Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor

Comments Published on ICLR 2024

AI Literacy in Low-Resource Languages:Insights from creating AI in Yoruba videos

Wuraola Oyewusi

Comments Accepted at the Global AI Cultures Workshop, ICLR 2024

GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks

Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas Mayr

Comments Accepted at ICLR 2024 (Tiny Papers Track)

Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI

Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar

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

CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?

Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai

Comments 32 pages, 20 figures, 7 tables

Journal ref ICLR 2024

Enhancing Data Quality in Federated Fine-Tuning of Foundation Models

Wanru Zhao, Yaxin Du, Nicholas Donald Lane, Siheng Chen, Yanfeng Wang

Comments Accepted at ICLR 2024 Workshop on Navigating and Addressing Data Problems for Foundation Models (DPFM)

Mastering Memory Tasks with World Models

Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, Sarath Chandar

Comments Published as a conference paper at The International Conference on Learning Representations 2024

Preference optimization of protein language models as a multi-objective binder design paradigm

Pouria Mistani, Venkatesh Mysore

Comments Published at the GEM workshop, ICLR 2024. Generative and Experimental Perspectives for Biomolecular Design (https://www.gembio.ai/)