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Prompting LLMs to Compose Meta-Review Drafts from Peer-Review Narratives of Scholarly Manuscripts
Feb. 27, 2024, 5:42 a.m. | Shubhra Kanti Karmaker Santu, Sanjeev Kumar Sinha, Naman Bansal, Alex Knipper, Souvika Sarkar, John Salvador, Yash Mahajan, Sri Guttikonda, Mousumi Ak
cs.LG updates on arXiv.org arxiv.org
Abstract: One of the most important yet onerous tasks in the academic peer-reviewing process is composing meta-reviews, which involves understanding the core contributions, strengths, and weaknesses of a scholarly manuscript based on peer-review narratives from multiple experts and then summarizing those multiple experts' perspectives into a concise holistic overview. Given the latest major developments in generative AI, especially Large Language Models (LLMs), it is very compelling to rigorously study the utility of LLMs in generating such …
abstract academic arxiv core cs.ai cs.cl cs.lg cs.ne experts llms meta multiple peer peer-review perspectives process prompting prompting llms review reviews summarizing tasks type understanding
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