ICLR

Adversarial Robustness for Visual Grounding of Multimodal Large Language Models

Kuofeng Gao, Yang Bai, Jiawang Bai, Yong Yang, Shu-Tao Xia

Comments ICLR 2024 Workshop on Reliable and Responsible Foundation Models

Whole-Song Hierarchical Generation of Symbolic Music Using Cascaded Diffusion Models

Ziyu Wang, Lejun Min, Gus Xia

Comments Proceedings of the International Conference on Learning Representations (ICLR 2024)

Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints

Jian Chen, Ruiyi Zhang, Yufan Zhou, Rajiv Jain, Zhiqiang Xu, Ryan Rossi, Changyou Chen

Comments Accepted by ICLR 2024

Querying Easily Flip-flopped Samples for Deep Active Learning

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

Comments 34 pages, 17 figures, 5 tables. Accepted to the 12th International Conference on Learning Representations (ICLR 2024) (ver2: fixed some typos and improved some parts of the writing)

More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory

James B. Simon, Dhruva Karkada, Nikhil Ghosh, Mikhail Belkin

Comments Appeared in ICLR 2024

BatteryML:An Open-source platform for Machine Learning on Battery Degradation

Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian

Journal ref International Conference on Learning Representations (ICLR) 2024

Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models

Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang

Comments Accepted by ICLR 2024 Poster

Synthpop++: A Hybrid Framework for Generating A Country-scale Synthetic Population

Bhavesh Neekhra, Kshitij Kapoor, Debayan Gupta

Comments 9 pages, 6 figures, Accepted for oral presentation at AI4ABM workshop at ICLR 2023

A Resource Model For Neural Scaling Law

Jinyeop Song, Ziming Liu, Max Tegmark, Jeff Gore

Comments 10 pages, 8 figures, Published as a workshop paper at ICLR 2024

On the Shape of Brainscores for Large Language Models (LLMs)

Jingkai Li

Comments Published as a workshop paper at ICLR AGI Workshop 2024

Tangent Transformers for Composition, Privacy and Removal

Tian Yu Liu, Aditya Golatkar, Stefano Soatto

Comments Published at the International Conference on Learning Representations (ICLR) 2024. Code available at: https://github.com/tianyu139/tangent-model-composition

Learning Multi-Agent Communication from Graph Modeling Perspective

Shengchao Hu, Li Shen, Ya Zhang, Dacheng Tao

Comments Published at ICLR 2024

Direct Alignment of Draft Model for Speculative Decoding with Chat-Fine-Tuned LLMs

Raghavv Goel, Mukul Gagrani, Wonseok Jeon, Junyoung Park, Mingu Lee, Christopher Lott

Comments 8 pages, 3 figures, Published at the ICLR 2024 Workshop on Understanding of Foundation Models (ME-FoMo)

lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning

Shangmin Guo, Yi Ren, Stefano V. Albrecht, Kenny Smith

Comments ICLR-2024

Efficient and Scalable Graph Generation through Iterative Local Expansion

Andreas Bergmeister, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer

Comments Published as a conference paper at ICLR 2024

SD-NAE: Generating Natural Adversarial Examples with Stable Diffusion

Yueqian Lin, Jingyang Zhang, Yiran Chen, Hai Li

Comments Accepted by ICLR 2024 TinyPapers

Squeezing Lemons with Hammers: An Evaluation of AutoML and Tabular Deep Learning for Data-Scarce Classification Applications

Ricardo Knauer, Erik Rodner

Comments ICLR 2024 Workshop on Practical ML for Low Resource Settings

Hijacking Context in Large Multi-modal Models

Joonhyun Jeong

Comments Technical Report. Preprint

Journal ref ICLR 2024 Workshop on Reliable and Responsible Foundation Models

CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling

Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley, Otmar Hilliges, Romann M. Weber

Comments Published as a conference paper at ICLR 2024

Journal ref The Twelfth International Conference on Learning Representations (ICLR 2024)

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

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

Comments Accepted to The Twelfth International Conference on Learning Representations, ICLR 2024

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

Hien Dang, Tho Tran, Tan Nguyen, Nhat Ho

Comments Accepted (Poster) at the Twelfth International Conference on Learning Representations

Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction

Aleix Lafita, Ferran Gonzalez, Mahmoud Hossam, Paul Smyth, Jacob Deasy, Ari Allyn-Feuer, Daniel Seaton, Stephen Young

Comments Machine Learning for Genomics Explorations workshop at ICLR 2024

Enhancing Language Models for Financial Relation Extraction with Named Entities and Part-of-Speech

Menglin Li, Kwan Hui Lim

Comments Accepted to ICLR 2024 Tiny Paper Track

Protein Representation Learning by Capturing Protein Sequence-Structure-Function Relationship

Eunji Ko, Seul Lee, Minseon Kim, Dongki Kim

Comments ICLR 2024 MLGenX Workshop (Spotlight)

PROflow: An iterative refinement model for PROTAC-induced structure prediction

Bo Qiang, Wenxian Shi, Yuxuan Song, Menghua Wu

Comments Published at the GEM workshop, ICLR 2024

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

Hengrui Zhang, Jiani Zhang, Balasubramaniam Srinivasan, Zhengyuan Shen, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis

Comments Accepted by ICLR 2024 (Oral Presentation). Code is available at: https://github.com/amazon-science/tabsyn

Unveiling the Pitfalls of Knowledge Editing for Large Language Models

Zhoubo Li, Ningyu Zhang, Yunzhi Yao, Mengru Wang, Xi Chen, Huajun Chen

Comments ICLR 2024

Efficient Dynamics Modeling in Interactive Environments with Koopman Theory

Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar, Kaleem Siddiqi, Siamak Ravanbakhsh

Comments Accepted to ICLR 2024 and EWRL 2023

Learning to Extend Molecular Scaffolds with Structural Motifs

Krzysztof Maziarz, Henry Jackson-Flux, Pashmina Cameron, Finton Sirockin, Nadine Schneider, Nikolaus Stiefl, Marwin Segler, Marc Brockschmidt

Comments Published at the 10th International Conference on Learning Representations (ICLR 2022)

Confidence Calibration and Rationalization for LLMs via Multi-Agent Deliberation

Ruixin Yang, Dheeraj Rajagopal, Shirley Anugrah Hayati, Bin Hu, Dongyeop Kang

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