Neural dialog state tracker for large ontologies by attention mechanism. - Youngsoo Jang; Jiyeon Ham; Byung-Jun Lee 001; Youngjae Chang 001; Kee-Eung Kim (SLT, 2016)

Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. - Jongmin Lee 004; Youngsoo Jang; Pascal Poupart; Kee-Eung Kim (IJCAI, 2017)

Cross-Language Neural Dialog State Tracker for Large Ontologies Using Hierarchical Attention. - Youngsoo Jang; Jiyeon Ham; Byung-Jun Lee 001; Kee-Eung Kim (IEEE ACM Trans. Audio Speech Lang. Process., 2018)

Trust Region Sequential Variational Inference. - Geon-hyeong Kim; Youngsoo Jang; Jongmin Lee 004; Wonseok Jeon; Hongseok Yang; Kee-Eung Kim (ACML, 2019)

PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules. - Youngsoo Jang; Jongmin Lee 004; Jaeyoung Park; Kyeng-Hun Lee; Pierre Lison; Kee-Eung Kim (EMNLP/IJCNLP (3), 2019)

Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues. - Youngsoo Jang; Jongmin Lee 004; Kee-Eung Kim (AAAI, 2020)

End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2. - DongHoon Ham; Jeong-Gwan Lee; Youngsoo Jang; Kee-Eung Kim (ACL, 2020)

Variational Inference for Sequential Data with Future Likelihood Estimates. - Geon-Hyeong Kim; Youngsoo Jang; Hongseok Yang; Kee-Eung Kim (ICML, 2020)

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

GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems. - Youngsoo Jang; Jongmin Lee 004; Kee-Eung Kim (ICLR, 2022)

LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation. - Geon-Hyeong Kim; Jongmin Lee 004; Youngsoo Jang; Hongseok Yang; Kee-Eung Kim (NeurIPS, 2022)

LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation. - Geon-Hyeong Kim; Jongmin Lee 004; Youngsoo Jang; Hongseok Yang; Kee-Eung Kim (CoRR, 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)

SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations. - Youngsoo Jang; Geon-Hyeong Kim; Jongmin Lee 004; Sungryull Sohn; Byoungjip Kim; Honglak Lee; Moontae Lee (NeurIPS, 2023)

Semantic Skill Grounding for Embodied Instruction-Following in Cross-Domain Environments. - Sangwoo Shin; Seunghyun Kim; Youngsoo Jang; Moontae Lee; Honguk Woo (ACL (Findings), 2024)

Show, Think, and Tell: Thought-Augmented Fine-Tuning of Large Language Models for Video Captioning. - Byoungjip Kim; Dasol Hwang; Sungjun Cho; Youngsoo Jang; Honglak Lee; Moontae Lee (CVPR Workshops, 2024)

Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking. - Byoungjip Kim; Youngsoo Jang; Lajanugen Logeswaran; Geon-Hyeong Kim; Yu Jin Kim; Honglak Lee; Moontae Lee (EMNLP (Findings), 2024)

Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration. - Youngsoo Jang; Geon-Hyeong Kim; Byoungjip Kim; Yu Jin Kim; Honglak Lee; Moontae Lee (ICML, 2024)

Reinforcement Learning from Reflective Feedback (RLRF): Aligning and Improving LLMs via Fine-Grained Self-Reflection. - Kyungjae Lee 002; Dasol Hwang; Sunghyun Park 005; Youngsoo Jang; Moontae Lee (CoRR, 2024)

SafeDPO: A Simple Approach to Direct Preference Optimization with Enhanced Safety. - Geon-Hyeong Kim; Youngsoo Jang; Yu Jin Kim; Byoungjip Kim; Honglak Lee; Kyunghoon Bae; Moontae Lee (CoRR, 2025)

Online Pre-Training for Offline-to-Online Reinforcement Learning. - Yongjae Shin; Jeonghye Kim; Whiyoung Jung; Sunghoon Hong; Deunsol Yoon; Youngsoo Jang; Geonhyeong Kim; Jongseong Chae; Youngchul Sung; Kanghoon Lee; Woohyung Lim (CoRR, 2025)