Yun-Shiuan Chuang
Orcid: 0000-0002-3392-6411
According to our database1,
Yun-Shiuan Chuang authored at least 23 papers
between 2020 and 2026.
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Bibliography
2026
Toward Scalable Verifiable Reward: Proxy State-Based Evaluation for Multi-turn Tool-Calling LLM Agents.
CoRR, February, 2026
2025
DEBATE: A Large-Scale Benchmark for Role-Playing LLM Agents in Multi-Agent, Long-Form Debates.
CoRR, October, 2025
Top. Cogn. Sci., January, 2025
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025
2024
Optimizing Social Media Annotation of HPV Vaccine Skepticism and Misinformation Using Large Language Models: An Experimental Evaluation of In-Context Learning and Fine-Tuning Stance Detection Across Multiple Models.
CoRR, 2024
Beyond Demographics: Aligning Role-playing LLM-based Agents Using Human Belief Networks.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024
Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024
Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024
The Wisdom of Partisan Crowds: Comparing Collective Intelligence in Humans and LLM-based Agents.
Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024
Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024
2023
Evaluating LLM Agent Group Dynamics against Human Group Dynamics: A Case Study on Wisdom of Partisan Crowds.
CoRR, 2023
CoRR, 2023
Decoding Affect in Dyadic Conversations: Leveraging Semantic Similarity through Sentence Embedding.
CoRR, 2023
Tutorials on Stance Detection using Pre-trained Language Models: Fine-tuning BERT and Prompting Large Language Models.
CoRR, 2023
Computational Agent-based Models in Opinion Dynamics: A Survey on Social Simulations and Empirical Studies.
CoRR, 2023
2021
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners.
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021
2020
Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners.
CoRR, 2020
Using Machine Theory of Mind to Learn Agent Social Network Structures from Observed Interactive Behaviors with Targets.
Proceedings of the 29th IEEE International Conference on Robot and Human Interactive Communication, 2020
Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020