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publications
Automatic Assessment and Identification of Leadership in College Students
Published in IEEE Access, 2022
This paper introduces LAIGA , a machine learning-based framework for automatically and passively assessing and identifying leaders in college students from their academic profiles and behavior in the learning management system (LMS).
Pongpaichet, S., Nirunwiroj, K., & Tuarob, S. (2022). Automatic assessment and identification of leadership in college students. IEEE Access, 10, 79041–79060. https://doi.org/10.1109/ACCESS.2022.3193935
Chitchat Bots: A Comparative Study and Behavioral Analysis of Large Language Models Using Epistemic Network Analysis
Published in Advances in Quantitative Ethnography: Fifth International Conference on Quantitative Ethnography: Conference Proceedings Supplement, 2023
This study aims to investigate the behavior and interaction between two prominent large language models: ChatGPT (GPT3.5) developed by OpenAI and Bard AI developed by Google.
Nirunwiroj, K. (2023). Chitchat bots: a comparative study and behavioral analysis of large language models using epistemic network analysis. Advances in Quantitative Ethnography: Fifth International Conference on Quantitative Ethnography: Conference Proceedings Supplement, 154-157 https://www.qesoc.org/images/pdf/ICQE23_Supplement_Proceedings.pdf#page=157
Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks
Published in EMNLP 2024 Findings and NeurIPS 2024 Workshop on Behavioral ML, 2024
Chuang, Y. S., Nirunwiroj, K.†, Studdiford, Z.†, Goyal, A., Frigo, V. V., Yang, S., Shah, D., Hu, J., & Rogers, T. T. (2024). Beyond demographics: Aligning role-playing LLM-based agents using human belief networks. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 14010–14026, Miami, Florida, USA. Association for Computational Linguistics.
Chuang, Y. S., Nirunwiroj, K.†, Studdiford, Z.†, Goyal, A., Frigo, V. V., Yang, S., Shah, D., Hu, J., & Rogers, T. T. (2024). Beyond demographics: Aligning role-playing LLM-based agents using human belief networks. NeurIPS 2024 Workshop on Behavioral Machine Learning. https://arxiv.org/abs/2406.17232