ICML

Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks

Haoyu Li, Shichang Zhang, Longwen Tang, Mathieu Bauchy, Yizhou Sun

Comments ICML 2024. Code available at https://github.com/haoyuli02/SymGNN

A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks

Nicholas Monath, Will Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer

Comments ICML 2024

Interpreting and Improving Large Language Models in Arithmetic Calculation

Wei Zhang, Chaoqun Wan, Yonggang Zhang, Yiu-ming Cheung, Xinmei Tian, Xu Shen, Jieping Ye

Comments Accepted by ICML 2024 (oral)

Quantum Implicit Neural Representations

Jiaming Zhao, Wenbo Qiao, Peng Zhang, Hui Gao

Comments This paper was accepted by icml 2024

AlphaFold Meets Flow Matching for Generating Protein Ensembles

Bowen Jing, Bonnie Berger, Tommi Jaakkola

Comments ICML 2024

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback

Harrison Lee, Samrat Phatale, Hassan Mansoor, Thomas Mesnard, Johan Ferret, Kellie Lu, Colton Bishop, Ethan Hall, Victor Carbune, Abhinav Rastogi, Sushant Prakash

Comments Presented at ICML 2024

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:26874-26901, 2024

INSTA-YOLO: Real-Time Instance Segmentation

Eslam Mohamed, Abdelrahman Shaker, Ahmad El-Sallab, Mayada Hadhoud

Comments Accepted at ICML-2020 Workshop on AI for Autonomous Driving

Gradient-Free Method for Heavily Constrained Nonconvex Optimization

Wanli Shi, Hongchang Gao, Bin Gu

Comments 21 page, 12 figures, conference

Journal ref International Conference on Machine Learning. PMLR, 2022: 19935-19955

Double Momentum Method for Lower-Level Constrained Bilevel Optimization

Wanli Shi, Yi Chang, Bin Gu

Comments 27pages, 9 figures

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:44838-44864, 2024

Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?

Shayne Longpre, Robert Mahari, Naana Obeng-Marnu, William Brannon, Tobin South, Katy Gero, Sandy Pentland, Jad Kabbara

Comments ICML 2024 camera-ready version (Spotlight paper). 9 pages, 2 tables

Journal ref Proceedings of ICML 2024, in PMLR 235:32711-32725. URL: https://proceedings.mlr.press/v235/longpre24b.html

VA-learning as a more efficient alternative to Q-learning

Yunhao Tang, Rémi Munos, Mark Rowland, Michal Valko

Comments Accepted to ICML 2023 as a conference paper

Equation identification for fluid flows via physics-informed neural networks

Alexander New, Marisel Villafañe-Delgado, Charles Shugert

Comments Published at ICML 2024 AI4Science: https://openreview.net/forum?id=XsvCLEYH3O

Self-supervised learning for crystal property prediction via denoising

Alexander New, Nam Q. Le, Michael J. Pekala, Christopher D. Stiles

Comments Published at ICML 2024 AI4Science: https://openreview.net/forum?id=yML9ufAEoV

Differentiability and Optimization of Multiparameter Persistent Homology

Luis Scoccola, Siddharth Setlur, David Loiseaux, Mathieu Carrière, Steve Oudot

Comments 13 pages + 13 page appendix, 8 figures. v2: update references and fix typos

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:43986-44011, 2024

Scaling Up Diffusion and Flow-based XGBoost Models

Jesse C. Cresswell, Taewoo Kim

Comments Presented at ICML 2024 Workshop on AI for Science

LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits

Chen-Chia Chang, Yikang Shen, Shaoze Fan, Jing Li, Shun Zhang, Ningyuan Cao, Yiran Chen, Xin Zhang

Comments Proceedings of the 41st International Conference on Machine Learning, PMLR 235:6253-6262 https://proceedings.mlr.press/v235/chang24c.html

Journal ref Proceedings of the 41st International Conference on Machine Learning, PMLR 235:6253-6262, 2024

Mitigating Label Noise on Graph via Topological Sample Selection

Yuhao Wu, Jiangchao Yao, Xiaobo Xia, Jun Yu, Ruxin Wang, Bo Han, Tongliang Liu

Comments ICML 2024

Standardized Interpretable Fairness Measures for Continuous Risk Scores

Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann

Journal ref Proceedings of the 41st International Conference on Machine Learning, 2024

Language Adaptation on a Tight Academic Compute Budget: Tokenizer Swapping Works and Pure bfloat16 Is Enough

Konstantin Dobler, Gerard de Melo

Comments WANT@ICML 2024

Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis

Sakhinana Sagar Srinivas, Chidaksh Ravuru, Geethan Sannidhi, Venkataramana Runkana

Comments Paper published at ICML 2024 Workshop on Foundation Models in the Wild

Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries

Amine Ouasfi, Adnane Boukhayma

Comments ICML 2024

Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference

Jiaming Tang, Yilong Zhao, Kan Zhu, Guangxuan Xiao, Baris Kasikci, Song Han

Comments ICML 2024

Minimum-Norm Interpolation Under Covariate Shift

Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu

Comments The Forty-first International Conference on Machine Learning (ICML 2024)

Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube

Kausik Lakkaraju, Vedant Khandelwal, Biplav Srivastava, Forest Agostinelli, Hengtao Tang, Prathamjeet Singh, Dezhi Wu, Matt Irvin, Ashish Kundu

Comments Accepted at 'Neural Conversational AI Workshop - What's left to TEACH (Trustworthy, Enhanced, Adaptable, Capable, and Human-centric) chatbots?' at ICML 2023

Split-and-Denoise: Protect large language model inference with local differential privacy

Peihua Mai, Ran Yan, Zhe Huang, Youjia Yang, Yan Pang

Comments Proceedings of the 41st International Conference on Machine Learning, 22 pages

Delving into Differentially Private Transformer

Youlong Ding, Xueyang Wu, Yining Meng, Yonggang Luo, Hao Wang, Weike Pan

Comments ICML 2024

Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations

GuanWen Qiu, Da Kuang, Surbhi Goel

Comments Accepted to ICML 2024 with the title:"Complexity Matters: Feature Learning in the Presence of Spurious Correlations". Fixed fig caption

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value

Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

Comments Accepted by ICML 2024 Conference

Sample Amplification: Increasing Dataset Size even when Learning is Impossible

Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant

Comments ICML 2020 (this version includes edits to clarify minor missing or incorrect details)

Foundational Model for Electron Micrograph Analysis: Instruction-Tuning Small-Scale Language-and-Vision Assistant for Enterprise Adoption

Sakhinana Sagar Srinivas, Chidaksh Ravuru, Geethan Sannidhi, Venkataramana Runkana

Comments Our paper is published at ICML 2024 Workshop ML for Life and Material Science: From Theory to Industry Applications, Vienna, Austria