4 papers
DeliChess: A Multi-party Dialogue Dataset for Deliberation in Chess Puzzle Solving
Xiaochen Zhu, Georgi Karadzhov, Tom Stafford +1
Multi-party dialogue is a critical setting for studying collaborative reasoning and decision-making, yet existing datasets rarely focus on structured, reasoning-intensive tasks. We…
Demystifying Multi-Agent Debate: The Role of Confidence and Diversity
Xiaochen Zhu, Caiqi Zhang, Yizhou Chi +3
Multi-agent debate (MAD) is widely used to improve large language model (LLM) performance through test-time scaling, yet recent work shows that vanilla MAD often underperforms simp…
Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems
Jooyoung Lee, Xiaochen Zhu, Georgi Karadzhov +3
The proliferation of generative models has presented significant challenges in distinguishing authentic human-authored content from deepfake content. Collaborative human efforts, a…
Conformity in Large Language Models
Xiaochen Zhu, Caiqi Zhang, Tom Stafford +2
The conformity effect describes the tendency of individuals to align their responses with the majority. Studying this bias in large language models (LLMs) is crucial, as LLMs are i…