Papers by Yizhou Chi
Demystifying Multi-Agent Debate: The Role of Confidence and Diversity (2026.findings-acl)
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| Challenge: | Multi-agent debate (MAD) is widely used to improve large language models' (LLMs) reasoning and test-time scaling. |
| Approach: | They propose a diversity-aware initialisation that selects a more diverse pool of candidate answers, increasing the likelihood that a correct hypothesis is present at the start of debate. |
| Outcome: | The proposed protocol outperforms vanilla MAD and majority vote on six reasoning-oriented QA benchmarks. |
ThoughtSculpt: Reasoning with Intermediate Revision and Search (2025.findings-naacl)
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| Challenge: | THOUGHTSCULPT is a general reasoning and search method for tasks with outputs that can be decomposed into components. |
| Approach: | They propose a general reasoning and search method for tasks with outputs that can be decomposed into components. |
| Outcome: | THOUGHTSCULPT outperforms state-of-the-art reasoning methods on three tasks . authors show that distinct prompting strategies can influence the performance of LLMs . |