Youngsoo Jang

Notice

I am actively recruiting motivated research interns and graduate students (M.S./Ph.D.) who are passionate about reinforcement learning and large language models. If you are interested, please feel free to email me with your CV and academic transcript: youngsoo.jang [at] unist.ac.kr

Education

• 2018.03 - 2022.08: Ph.D. in Computer Science, KAIST, Republic of Korea (Advisor: Prof. Kee-Eung Kim)

• 2016.03 - 2018.02: M.S. in Computer Science, KAIST, Republic of Korea (Advisor: Prof. Kee-Eung Kim)

• 2011.02 - 2016.02: B.S. in Mathematical Science and Computer Science (Double Major), KAIST, Republic of Korea

Work Experience

• 2025.09 - Present: Assistant Professor at UNIST (AIGS & CSE)

• 2022.08 - 2025.08: Research Scientist (Code LLM & RL Squad Leader) at LG AI Research, Superintelligence Lab (Prev: Advanced ML Lab)

Publications

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, and Moontae Lee

• Preprint, Under review at NeurIPS 2025

Online Pre-Training for Offline-to-Online Reinforcement Learning

• Yongjae Shin, Jeonghye Kim, Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Youngsoo Jang, Geon-Hyeong Kim, Jongseong Chae, Youngchul Sung, Kanghoon Lee, and Woohyung Lim

• Proceedings of International Conference on Machine Learning (ICML). 2025

Reinforcement Learning from Reflective Feedback (RLRF): Aligning and Improving LLMs via Fine-Grained Self-Reflection

• Kyungjae Lee*, Dasol Hwang*, Sunghyun Park*, Youngsoo Jang, and Moontae Lee

• arXiv preprint, Under review. 2025

Prospector: Improving LLM Agents with Self-Asking and Trajectory Ranking

• Byoungjip Kim, Youngsoo Jang, Lajanugen Logeswaran, Geon-Hyeong Kim, Yu Jin Kim, Honglak Lee, and Moontae Lee

• Conference on Empirical Methods in Natural Language Processing (EMNLP) Findings. 2024

• Proceedings of Neural Information Processing Systems (NeurIPS) Foundation Models for Decision Making Workshop. 2023

Semantic Skill Grounding for Embodied Instruction-Following in Cross-Domain Environments

• Sangwoo Shin*, SeungHyun Kim*, Youngsoo Jang, Moontae Lee, and Honguk Woo (*: equal contribution)

• Association for Computational Linguistics (ACL) 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, and Moontae Lee

• Proceedings of International Conference on Machine Learning (ICML). 2024

• International Conference on Learning Representations (ICLR) Workshop on Generative Models for Decision Making. 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

• The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshop on Multi-Modal Foundation Models. 2024

SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations

• Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, and Moontae Lee

• Proceedings of Neural Information Processing Systems (NeurIPS). 2023

Information-Theoretic State Space Model for Multi-View Reinforcement Learning

• HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-Hyeong Kim, Seunghoon Hong, and Kee-Eung Kim

• Proceedings of International Conference on Machine Learning (ICML). 2023 

LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation

• Geon-Hyeong Kim*, Jongmin Lee*, Youngsoo Jang, Hongseok Yang, and Kee-Eung Kim (*: equal contribution)

• Proceedings of Neural Information Processing Systems (NeurIPS). 2022

GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems

• Youngsoo Jang, Jongmin Lee, and Kee-Eung Kim

• International Conference on Learning Representations (ICLR). 2022

Monte-Carlo Planning and Learning with Language Action Value Estimates

• Youngsoo Jang, Seokin Seo, Jongmin Lee, and Kee-Eung Kim

• International Conference on Learning Representations (ICLR). 2021

Variational Inference for Sequential Data with Future Likelihood Estimates

• Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, and Kee-Eung Kim

• Proceedings of International Conference on Machine Learning (ICML). 2020

End-to-End Neural Pipeline for Goal-Oriented Dialogue System using GPT-2

• Donghoon Ham*, Jeong-Gwan Lee*, Youngsoo Jang, and Kee-Eung Kim (*: equal contribution)

• Proceedings of Association for Computational Linguistics (ACL). 2020

• Proceedings of AAAI Conference on Artificial Intelligence (AAAI) DSTC8 Workshop. 2020

• 1st place on 8th Dialog System Technology Challenge (DSTC8) Multi-domain Task Completion Track, 2019

Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues

• Youngsoo Jang, Jongmin Lee, and Kee-Eung Kim 

• Proceedings of AAAI Conference on Artificial Intelligence (AAAI). 2020

• Proceedings of Neural Information Processing Systems (NeurIPS) Conversational AI Workshop. 2019 (oral presentation)

Trust Region Sequential Variational Inference

• Geon-Hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, and Kee-Eung Kim

• Proceedings of Asian Conference on Machine Learning (ACML). 2019

PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Systems with Probabilistic Rules

• Youngsoo Jang*, Jongmin Lee*, Jaeyoung Park*, Kyeng-Hun Lee, Pierre Lison, and KeeEung Kim (*: equal contribution)

• Proceedings of Empirical Methods in Natural Language Processing (EMNLP), System Demonstrations. 2019

Cross-language Neural Dialog State Tracker for Large Ontologies using Hierarchical Attention

• Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, and Kee-Eung Kim

• IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP). 2018

Constrained Bayesian Reinforcement Learning via Approximate Linear Programming

• Jongmin Lee, Youngsoo Jang, Pascal Poupart, and Kee-Eung Kim

• Proceedings of International Joint Conference on Artificial Intelligence (IJCAI). 2017

• ECML-PKDD Workshop on Scaling-Up Reinforcement Learning (SURL). 2017

Neural Dialog State Tracker for Large Ontologies by Attention Mechanism

• Youngsoo Jang*, Jiyeon Ham*, Byung-Jun Lee, Youngjae Chang, and Kee-Eung Kim (*: equal contribution)

• IEEE Workshop on Spoken Language Technology (SLT). 2016 / 3rd place on 5th Dialog State Tracking Challenge (DSTC)

Awards and Honors

• NeurIPS Outstanding Reviewer Award, 2021

• Qualcomm-KAIST Innovation Awards, Qualcomm, 2019 (awarded $5,000)

• 1st place on 8th Dialog System Technology Challenge (DSTC8) Multi-domain Task Completion Track, 2019

• Naver Ph.D. Fellowship, NAVER, 2018 (awarded $5,000)

• 3rd place on 5th Dialog State Tracking Challenge (DSTC5), 2016

• Best TA Award, Introduction to Programming (CS101, 2016 Spring), School of Computing, KAIST, Sep. 2016

Academic Talks

Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration

• 2024. 07. 23. ICML 2024, Vienna, Austria

SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations

• 2023. 12. 15. NeurIPS 2023, New Orleans, USA

GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems

• 2022. 04. 26. ICLR 2022, Virtual

• 2022. 05. 11. NAVER, Virtual

Monte-Carlo Planning and Learning with Language Action Value Estimates

• 2021. 05. 04. ICLR 2021 ML in Korea, Virtual

• 2021. 05. 04. ICLR 2021, Virtual

Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues

• 2020. 07. 13. KAKAO Brain, Pangyo, Korea

• 2020. 02. 11. AAAI Conference on Artificial Intelligence, New York, USA

• 2019. 12. 14. NeurIPS Conversational AI Workshop 2019, Vancouver, Canada

• 2019. 11. 29. Qualcomm-KAIST Innovation Award 2019, KAIST, Korea

• 2019. 09. 27. KAKAO, Jeju, Korea

Teaching Experiences

• Machine Learning (CS376), TA, KAIST, 2019

• Counselor Assistant (CA), KAIST, 2019

• Introduction to Programming (CS101), Head TA, KAIST, 2018

• Data Structure (CS206), TA, KAIST, 2016

• Introduction to Programming (CS101), TA, KAIST, 2016

Academic Services

• NeurIPS Reviewer

• ICML Reviewer

• ICLR Reviewer

• AAAI Reviewer

• ACL Reviewer

• EMNLP Reviewer

• NAACL Reviewer