Youngsoo Jang

Ph.D. Candidate @ KAIST AILAB

Research Interest: Goal-Oriented Dialogue Generation, Dialogue System, Reinforcement Learning

Email: ysjang@ai.kaist.ac.kr

Education

  • 2018.03 - Present: 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

Publications

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 (accepted)

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 (accepted)
  • 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

  • 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

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

  • 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

Reviewer

  • AAAI (2019, 2020)
  • ICLR (2020)