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HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Fri, 31 Oct 2025 05:30:05 GMT access-control-allow-origin: * strict-transport-security: max-age=31556952 etag: W/"6904495d-428e" expires: Tue, 30 Dec 2025 06:13:07 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: 346D:3827E5:9BCB83:AEFCDB:69536B0F accept-ranges: bytes age: 0 date: Tue, 30 Dec 2025 06:03:07 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210036-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1767074587.290645,VS0,VE232 vary: Accept-Encoding x-fastly-request-id: 59b7d7c9ebde51c420e5103a65ded12f8ad3488b content-length: 4156 Ilgee Hong | Georgia Institute of Technology

Ilgee Hong

PhD Student
Georgia Institute of Technology
ihong39 (at) gatech.edu

About Me

Hello! I am a third-year Ph.D. student in Machine Learning at Georgia Institute of Technology, where I am advised by Prof. Tuo Zhao. Before attending GT, I received my M.S. degree in Statistics from the University of Chicago in 2023, where I was advised by Prof. Claire Donnat and Prof. Mladen Kolar. Prior to UChicago, I received my bachelor’s degree in Statistics at Yonsei University. At Yonsei, I was advised by Prof. Sangun Park.

Research Interests

My research primarily focuses on post-training methods for LLMs. I develop training and inference frameworks to improve their diverse capabilities, such as reasoning, instruction following, and multi-agent collaboration, especially through reinforcement learning.

Experience

Summer 2025: Research Intern, Google DeepMind
Fall 2024 - Spring 2025: Applied Scientist Intern, Amazon
Summer 2024: Research Intern, Microsoft

Publications

(* – authors alphabetically ordered; † – equal contribution)

Ask a Strong LLM Judge when Your Reward Model is Uncertain

Zhenghao Xu, Qin Lu, Qingru Zhang, Liang Qiu, Ilgee Hong, Changlong Yu, Wenlin Yao, Yao Liu, Haoming Jiang, Lihong Li, Hyokun Yun, Tuo Zhao

NeurIPS 2025

PDF Code
Think-RM: Enabling Long-Horizon Reasoning in Generative Reward Models

Ilgee Hong, Changlong Yu, Liang Qiu, Weixiang Yan, Zhenghao Xu, Haoming Jiang, Qingru Zhang, Qin Lu, Xin Liu, Chao Zhang, Tuo Zhao

NeurIPS 2025

PDF Code
SlimMoE: Structured Compression of Large MoE Models via Expert Slimming and Distillation

Zichong Li, Chen Liang, Zixuan Zhang, Ilgee Hong, Young Jin Kim, Weizhu Chen, Tuo Zhao

COLM 2025

PDF Code
Self-Rewarding PPO: Aligning Large Language Models with Demonstrations Only

Qingru Zhang, Liang Qiu, Ilgee Hong, Zhenghao Xu, Tianyi Liu, Shiyang Li, Rongzhi Zhang, Zheng Li, Lihong Li, Bing Yin, Chao Zhang, Jianshu Chen, Haoming Jiang, Tuo Zhao

COLM 2025

PDF Code
Discriminative Finetuning of Generative Large Language Models without Reward Models and Preference Data

Siqi Guo, Ilgee Hong, Vicente Balmaseda, Changlong Yu, Liang Qiu, Xin Liu, Haoming Jiang, Tuo Zhao, Tianbao Yang

ICML 2025

PDF Code
Robust Reinforcement Learning from Corrupted Human Feedback

Alexander Bukharin*, Ilgee Hong*, Haoming Jiang*, Zichong Li*, Qingru Zhang*, Zixuan Zhang*, Tuo Zhao*

NeurIPS 2024

PDF Code
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback

Ilgee Hong†, Zichong Li†, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao

NeurIPS 2024

PDF Code
Who Wrote this Code? Watermarking for Code Generation

Taehyun Lee†, Seokhee Hong†, Jaewoo Ahn, Ilgee Hong, Hwaran Lee, Sangdoo Yun, Jamin Shin, Gunhee Kim

ACL 2024

PDF Code
Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching

Ilgee Hong†, Sen Na†, Michael W. Mahoney, Mladen Kolar

ICML 2023

PDF Code
A Simplified Framework for Contrastive Learning for Node Representations

Ilgee Hong, Huy Tran, Claire Donnat

ACSSC 2023

PDF Code

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