Justin Chih-Yao Chen

CS Ph.D. Student @ UNC Chapel Hill

I am a first-year Ph.D. student at The University of North Carolina at Chapel Hill, advised by Prof. Mohit Bansal. Prior to that, I earned my master’s degree from the Data Science Program at National Taiwan University, advised by Dr. Lun-Wei Ku and Prof. Hsin-Hsi Chen. My research interests lie generally in Natural Language Processing, LLM Reasoning, Representation Learning and Knowledge Graph.

When I was an undergraduate, I double majored in Computer Science and Statistics at National Cheng Kung University. I had the pleasure of working close with Prof. Cheng-Te Li, on topics related to Relation Extraction and Recommendation System.

ReConcile: Multi-Round Discussion Among Diverse LLMs

Improve LLM reasoning via multi-round discussions.

Enhanced NLI-based Fact-Checking System

Prevent the NLI model from learning short cuts by using HEX projection.

Fine-grained Emotion Classification (FEC)

Incorporate hyperbolic space and Parrott's emotion model from psychology.


Ph.D. in Computer Science

UNC at Chapel Hill 2023-Present

M.S. in Data Science

National Taiwan University 2020-2022

B.S. in CS & B.B.A in Statistics

National Cheng Kung University 2016-2020

Work Experience

Institute of Information Science, Academia Sinica

Research Assistant NLPSA Lab • 2020-2022

Institute of Data Science, National Cheng Kung University

Research & Teaching Assistant NetAI Lab • 2017-2020


Data Scientist Intern Summer 2019


Oct 7, 2023 We have a paper accepted to EMNLP 2023!
Sep 22, 2023 We have a new preprint on arxiv!
May 4, 2023 We have two papers accepted to ACL 2023.
Apr 1, 2023 I will be joining MURGe-Lab and begin my Ph.D. journey!
Feb 16, 2023 We have a paper accepted to IEEE ICASSP 2023.
Aug 18, 2022 Taught advenced natural language processing course at Taiwan AI Academy

Selected Publications

  1. Preprint
    ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs
    Chen, Justin Chih-Yao, Saha, Swarnadeep, and Bansal, Mohit
  2. EMNLP’23
    Location-Aware Visual Question Generation with Lightweight Models
    Suwono, Nicholas Collin, Chen, Justin Chih-Yao, Hung, Tun Min, Huang, Ting-Hao Kenneth, Liao, I-Bin, Li, Yung-Hui, Ku, Lun-Wei, and Sun, Shao-Hua
  3. ACL’23
    HonestBait: Forward References for Attractive but Faithful Headline Generation
    In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2023
  4. ACL’23
    Label-Aware Hyperbolic Embeddings for Fine-grained Emotion Classification
    In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2023
  5. NAACL’21
    ZS-BERT: Towards Zero-Shot Relation Extraction with Attribute Representation Learning
    Chen, Chih-Yao, and Li, Cheng-Te
    In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies 2021