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Review Arcade: On the Human Alignment and Gameability of LLM Reviews

cs.AI updates on arXiv.org·
AI Analysis

A new study evaluates the effectiveness of LLM-generated reviews for scientific papers, revealing that while alignment with human reviews is limited, authors can improve their submissions through iterative revisions based on LLM feedback. This 'gaming' of LLM reviews has shown to significantly enhance scores for a notable percentage of papers.

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LLMACL Rolling ReviewGitHubAI

Originally reported by cs.AI updates on arXiv.org. Read the full article ↗

Review Arcade: On the Human Alignment and Gameability of LLM Reviews | AI Crypto Daily Wire