Publication

Yen-Shan Chen, Jing Jin, Peng-Ting Kuo, Chao-Wei Huang, Yun-Nung Chen, "LLMs are Biased Evaluators: But Not Biased for Retrieval Augmented Generation," presented at The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), Vienna, Austria, Jul 27 – Aug 1, 2025.

Peng-Ting Kuo, "When Right Makes Might: Rising Power and World Order," Political Science Quarterly Book Review, Vol.65, pages 21–24, 2022.

Ronan Tse-min Fu, Yu-Ning Chiu, Peng-Ting Kuo, "Explaining China's Security Policy under Xi Jinping: A Neoclassical Realist Approach"

Ronan Tse-min Fu, Peng-Ting Kuo, I-Lien Lee, Chia-Hsiang Han, Yu-Ning Chiu, "Democracy or Prosperity? A Cross-National Analysis of East Asian Countries"

Connor Jerzak, Peng-Ting Kuo, "The Continuous Global Leadership Project: A Verifiable AI Search Agent Methodology," presented at 2026 Texas Methods Conference, Texas, 2026.

Naofumi Fujimura, Nick Lin, Akitaka Matsuo, Peng-Ting Kuo, Ronan Tse-min Fu, Yutaka Shinada, "Divergent Paths from Electoral Institutions to Campaign Strategies: Analyzing Candidate Manifestos in Japan and Taiwan," presented at The 2025 IPSA World Congress, Seoul, South Korea, Jul 12–16, 2025.

Peng-Ting Kuo, Ronan Tse-min Fu, Nick Lin, "Electoral Reform and Campaign Tactics: A Machine Learning Analysis of Taiwanese Legislative Candidates' Manifestos," presented at The 16th International Conference on Parliamentary Studies, Taipei, Taiwan, Jun 15–16, 2024.

Yu-Hung Sun, Peng-Ting Kuo, Chun-Ming Tsui, Hong-Wung Wang, "From Human-Label to Auto-Label: An Automatic Classification Model for Legislators' Oral Questions," presented at The 16th International Conference on Parliamentary Studies, Taipei, Taiwan, Jun 15–16, 2024.

Su-Feng Cheng, Ronan Tse-min Fu, Peng-Ting Kuo, "Understanding the Impact of Election System Reform on Legislative Campaigning Strategies: A Machine Learning Approach," presented at the Annual Meeting of Japanese Association of Electoral Studies, Kochi, Japan, May 18–19, 2024.

Peng-Ting Kuo, Ronan Tse-min Fu, "Decoding Campaigning Strategies: A Machine Learning Approach to Understanding the Impact of Election Systems on Legislative Candidates," presented at The 81st Midwest Political Science Association Conference, Chicago, United States, Apr 4–7, 2024.