Ph.D. Student University of Southern California
Information Science Institute (ISI) [link]
dongho.lee@usc.edu Curriculum Vitae (Last Updated: 21 Apr 2022) Google scholar, Github, Twitter
Research Interests
Explanation-based Learning, Knowledge Graph, Information Extraction, Natural Language Understanding, Computer-supported Learning
Education
University of Southern California
Ph.D. in Computer Science, Aug 2021 – PRESENT, Advisor: Dr. Jay Pujara
MS in Computer Science, Aug 2018 – May 2020, Advisor: Dr. Xiang Ren
Sungkyunkwan University
BS in Computer Education, Mar 2012 – Feb 2018
Experiences
Microsoft Research
Research Intern, May 2022 – Aug 2022, Advisor: Dr. Sujay Kumar Jauhar
Upstage AI
AI Research Engineer, Aug 2021 – Mar 2022
USC ISI
Research Programmer 1, Sep 2020 – Aug 2021, Advisor: Dr. Ralph Weischedel
Awards and Scholarships
Best Paper Award, NAACL 2021 TrustNLP Workshop
Best Paper Award, KIPS 2018 Spring Conference
Academic Scholarship, Sungkyunkwan University (Fall 2016)
Preprints
AutoTriggER: Named Entity Recognition with Auxiliary Trigger Extraction
Dong-Ho Lee*, Ravi Kiran Selvam*, Sheikh Muhammad Sarwar, Bill Yuchen Lin, Mahak Agarwal, Fred Morstatter, Jay Pujara, Elizabeth Boschee, James Allan and Xiang Ren
WeaSuL@ICLR 2021, TrustNLP@NAACL 2021 (Best Paper Award) [link]
Research Papers in Conference Proceedings
Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER
Dong-Ho Lee, Akshen Kadakia*, Kangmin Tan*, Mahak Agarwal, Xinyu Feng, Takashi Shibuya, Ryosuke Mitani, Toshiyuki Sekiya, Jay Pujara and Xiang Ren
ACL 2022 [link] [Code] [Slides] [Poster]
Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-Modal Knowledge Transfer
Woojeong Jin*, Dong-Ho Lee*, Chenguang Zhu, Jay Pujara and Xiang Ren
ACL 2022 [link] [Code] [Slides] [Poster]
Perhaps PTLMs should go to School – A Task to Assess Open Book and Closed Book QA
Manuel Ciosici, Joe Cecil, Alex Hedges, Dong-Ho Lee, Marjorie Freedman and Ralph Weischedel
EMNLP 2021 [link]
Improving Text Auto-Completion with Next Phrase Prediction
Dong-Ho Lee, Zhiqiang Hu and Roy Ka-Wei Lee
EMNLP 2021 Findings [link]
ForecastQA: A Question Answering Challenge for Event Forecasting
Woojeong Jin, Suji Kim, Rahul Khanna, Dong-Ho Lee, Fred Morstatter, Aram Galstyan and Xiang Ren
ACL 2021 [link]
RiddleSense: Answering Riddle Questions as Commonsense
Bill Yuchen Lin, Ziyi Wu, Yichi Yang, Dong-Ho Lee and Xiang Ren
ACL 2021 Findings [link]
Pre-training Text-to-Text Transformers for Concept-Centric Common Sense
Wangchunshu Zhou*, Dong-Ho Lee*, Ravi kiran Selvam, Seyeon Lee, Bill Yuchen Lin and Xiang Ren
ICLR 2021 [link] [Project]
Machine-Assisted Script Curation
Manuel R Ciosici, Joseph Cummings, Mitchell DeHaven, Alex Hedges, Yash Kankanampati, Dong-Ho Lee, Ralph Weischedel and Marjorie Freedman
NAACL 2021 Demo Track [link]
TriggerNER: Label-Efficient Learning for Named Entity Recognition via Annotating Entity Triggers
Bill Yuchen Lin*, Dong-Ho Lee*, Ming Shen, Ryan Moreno, Xiao Huang, Prashant Shiralkar and Xiang Ren
ACL 2020 [link] [Project]
LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation
Dong-Ho Lee*, Rahul Khanna*, Bill Yuchen Lin, Jamin Chen, Seyeon Lee, Qinyuan Ye, Elizabeth Boschee, Leonardo Neves and Xiang Ren
ACL 2020 Demo Track [link] [Project]
AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging
Bill Yuchen Lin*, Dong-Ho Lee*, Frank F. Xu, Ouyu Lan and Xiang Ren
ACL 2019 Demo Track [link] [Github]
Journals
Fake news detection using deep learning
Dong-Ho Lee, Yu-Ri Kim, Hyeong-Jun Kim, Seung-Myun Park and Yu-Jun Yang
Journal of Information Processing System (JIPS) [link]
Dong-Ho Lee 