* indicates alphabetical order or equal contribution.

I can also be found on Google Scholar.

Full paper lists

Preprints

  • Chanwoo Park, Seungju Han, Xingzhi Guo, Asuman Ozdaglar, Kaiqing Zhang, Joo-Kyung Kim, “MAPoRL: Multi-Agent Post-Co-Training for Collaborative Large Language Models with Reinforcement Learning”, Submitted, pdf
  • Chanwoo Park, Mingyang Liu, Dingwen Kong, Kaiqing Zhang, Asuman Ozdaglar, “RLHF with Diverse Feedback via Personalization and Preference Aggregation”, Submitted.
  • Jaeyeon Kim, Chanwoo Park, Asuman Ozdaglar, Jelena Diakonikolas, Ernest K. Ryu, “Mirror Duality in Convex Optimization”, pdf
  • Gunmin Lee, Jae Seok Heo, Dohyeong Kim, Jeongwoo Oh, Minyoung Hwang, Chanwoo Park, Kyungjae Lee, Songhwai Oh, “SafeIL: Safety Constrained Imitation Learning for Autonomous Systems”, Submitted.

Published Papers

  • Chanwoo Park*, Xiangyu Liu*, Asuman Ozdaglar, Kaiqing Zhang, “Do LLM Agents Have Regret? A Case Study in Online Learning and Games”, pdf,, ICLR 2025, Oral presentation at How Far Are We From AGI, ICLR 2024, Invited Talk at INFORMS 2024
  • Hyunin Lee, Chanwoo Park, David Abel, Ming Jin, Javad Lavaei, Somayeh Sojoudi, “A Black Swan Hypothesis: the Role of Human Perception in Unchanging Environments”, ICLR 2025. pdf
  • Yubin Kim, Chawoo Park, Hyewon Jeong, Yik Siu Chan, Xuhai Xu, Daniel McDuff, Marzyeh Ghassemi, Cynthia Breazeal, Hae Won Park, “Adaptive Collaboration Strategy for LLMs in Medical Decision Making”, NeurIPS 2024, Oral, pdf
  • Chanwoo Park, Ernest K. Ryu, “Optimal First-Order Algorithms as a Function of Inequalities”, Journal of Machine Learning (JMLR) 2024 pdf
  • Minyoung Hwang, Luca Weihs, Chanwoo Park, Kimin Lee, Aniruddha Kembhavi, Kiana Ehsani, “Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences”, CVPR 2024, pdf
  • Chanwoo Park*, Kaiqing Zhang*, Asuman Ozdaglar, “Multi-Player Zero-Sum Markov Games with Networked Separable Interactions”, NeurIPS 2023, Invited Talk at INFORMS 2023 pdf
  • Jaeyeon Kim*, Asuman Ozdaglar*, Chanwoo Park*, Ernest K. Ryu*, “Time-Reversed Dissipation Induces Duality Between Minimizing Gradient Norm and Function Value”, NeurIPS 2023, (Oral presentation at Duality Principles for Modern ML, ICML 2023), pdf
  • Chanwoo Park*, Sangdoo Yun*, Sanghyuk Chun, “A Unified Analysis of Mixed Sample Data Augmentation: A Loss Function Perspective”, NeurIPS 2022pdf
  • Chanwoo Park, Jisun Park, Ernest K. Ryu, “Factor-$\sqrt{2}$ Acceleration of Accelerated Gradient Methods”, Applied Mathematics and Optimization, 2022 pdf
  • Chanwoo Park, Boram Kim, Taesung Park, “DeepHisCoM: Deep Learning based Pathway Analysis”, Briefings in Bioinformatics, 2022
  • Jongmin Lee, Chanwoo Park, Ernest K. Ryu, “A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast”, NeurIPS 2021 pdf
  • Chanwoo Park, Nan Jiang, Taesung Park, “Pure additive contribution of genetic variants to a risk prediction model using propensity score matching: application to type 2 diabetes”, Genomics & Informatics, Vol. 17, No. 4, Dec. 2019.