I’m interested in NLP, especially in parametric knowledge of LLMs.

Especially understanding (Evaluation on benchmark, membership attacking), unlocking (In-context learning, SFT, alignment learning, reasoning), and expanding (Continual learning) their parametric knowledge to meet ultimate human needs.

I’m currently start my research on VLM’s jailbreaking and LLM hallucination detection problems.

Check out my and my teammate’s PaperReview (e.g., Agent Survey, Recent Research Paper) and BlogPost here!

===================================== CV =====================================

Joonwon_CV.pdf

================================== LINKEDIN ==================================

www.linkedin.com

================================ HF (Open Source) ===============================

https://huggingface.co/lainshower

Education

MS in Graduate School of Artificial Intelligence, POSTECH. (2023.02 – 2025.02)

Bachelor's degree in Hotel &Tourism Management, Sejong University.(2017- 2023) (GPA: 4.37/4.5, Summa Cum Laude)

International Student in School of Hotel and Tourism Managment HongKong Polytechnic University (2018.09-2018.12)

Publications

• International

  • Joonwon Jang, Jaehee Kim, Wonbin Kweon, Hwanjo Yu. Verbosity-Aware Rationale Reduction: Effective Reduction of Redundant Rationale via Principled Criteria (Arxiv, ARR 2025 Feb)
  • Seonghyeon Lee, HeeJae Chon, Joonwon Jang, Dongha Lee, Hwanjo Yu. ******How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code (Arxiv, ARR 2025 Feb)
  • WooJoo Kim, Joonwon Jang, Jinyi Yu, Yunsu Jeon, and Hwanjo Yu. EPR: An Expert Behavior-enhanced Paper Ranking Framework for the Automotive Industry (EMNLP 2024 Workshop)
  • Seonghyeon Lee, Suyeon Kim, Joonwon Jang, Heejae Chon, Dongha Lee, Hwanjo Yu. Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation (EMNLP 2024 Findings)
  • Joonwon Jang, Sanghwan Jang, Wonbin Kweon, Minjin Jeon, and Hwanjo Yu. Rectifying Demonstration Shortcut in In-Context Learning, 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics. (NAACL 2024 Main)
  • Jaeyoung Lee, Joonwon Jang, and Misuk Kim. Hierarchical Graph Convolutional Network Approach for Detecting Low-Quality Documents, The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation. (LREC-COLING 2024)
  • Eunbi Choi, Yongrae Jo, Joel Jang, Joonwon Jang, and Minjoon Seo. Fixed Input Parameterization for Efficient Prompting, Findings of the Association for Computational Linguistics. (ACL 2023 Findings)
  • Joonwon Jang, Sung Il Kwag, and Young Dae Ko. Eco-friendly platooning operation algorithm of the autonomous vehicles*, Journal of Intelligent Transportation Systems: Technology, Planning, and Operations*. (JITS, 2023)
  • Joonwon Jang and Misuk Kim. Headline Token-based Discriminative Learning for Subheading Generation in News Article, The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL) findings. (EACL 2023 Findings)
  • Joonwon Jang, Minju Kim, Yoonsik Cho, and Misuk Kim. Detecting incongruent news headlines with auxiliary textual information, Expert Systems with Applications. (ESWA, 2022) (IF 6.954)

• Domestic

  • 장준원 & 김미숙 (2022). 추출 기반의 뉴스 부제목 생성 프레임워크
  • 장준원, 조하현, 이재영, & 김미숙. (2021). 제목과 본문이 다른 가짜뉴스 탐지를 위한 계층적 딥러닝 모델 개발 및 가짜 뉴스 데이터셋 구축. 한국정보과학회 학술발표논문집