Papers by Shixiang Tang

2 papers
Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System (2025.acl-long)

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Challenge: Recent AI methods have shown promise in tasks such as hypothesis generation and experimental design, but they fail to replicate the collaborative nature of real-world scientific practices.
Approach: They propose a virtual scientific system that mimics the collaborative nature of scientific research by organizing a team of agents to generate, evaluate, and refine research ideas.
Outcome: The proposed system outperforms the state-of-the-art method in producing new scientific ideas and offers valuable insights to guide future research.
ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition (2026.findings-acl)

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Challenge: Large language models have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses remains unexamined due to the lack of a dedicated benchmark.
Approach: They propose a benchmark for evaluating large language models on a sufficient set of scientific discovery sub-tasks.
Outcome: The proposed framework extracts critical components from papers across 12 disciplines with expert validation confirming its accuracy.

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