A Bayesian Approach to Generative Adversarial Imitation Learning. - Wonseok Jeon; Seokin Seo; Kee-Eung Kim (NeurIPS, 2018)

Monte-Carlo Planning and Learning with Language Action Value Estimates. - Youngsoo Jang; Seokin Seo; Jongmin Lee 004; Kee-Eung Kim (ICLR, 2021)

DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations. - Geon-Hyeong Kim; Seokin Seo; Jongmin Lee 004; Wonseok Jeon; HyeongJoo Hwang; Hongseok Yang; Kee-Eung Kim (ICLR, 2022)

Information-Theoretic State Space Model for Multi-View Reinforcement Learning. - HyeongJoo Hwang; Seokin Seo; Youngsoo Jang; Sungyoon Kim; Geon-Hyeong Kim; Seunghoon Hong; Kee-Eung Kim (ICML, 2023)

Regularized Behavior Cloning for Blocking the Leakage of Past Action Information. - Seokin Seo; HyeongJoo Hwang; Hongseok Yang; Kee-Eung Kim (NeurIPS, 2023)

Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction. - Seokin Seo; Byung-Jun Lee 001; Jongmin Lee 004; HyeongJoo Hwang; Hongseok Yang; Kee-Eung Kim (NeurIPS, 2024)

Zero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models. - Seongmin Lee 011; Jaewook Shin; Youngjin Ahn; Seokin Seo; Ohjoon Kwon; Kee-Eung Kim (CoRR, 2024)

Goal-Conditioned DPO: Prioritizing Safety in Misaligned Instructions. - Joo Bon Maeng; Seongmin Lee 011; Seokin Seo; Kee-Eung Kim (NAACL (Long Papers), 2025)