5 papers · 1 filter
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…
The effect of diversity on group decision-making
Georgi Karadzhov, Andreas Vlachos, Tom Stafford
We explore different aspects of cognitive diversity and its effect on the success of group deliberation. To evaluate this, we use 500 dialogues from small, online groups discussing…