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This paper introduces PRISMA-LLM, an empirically grounded framework for reporting AI-assisted systematic reviews, addressing inconsistencies in how LLMs and AI software are documented in review workflows.
This paper introduces intra-paper claim verification, a framework that uses LLMs to evaluate whether novelty claims in a paper are supported by its methodological evidence, addressing a gap in existing automated peer review systems. Human evaluation shows significant alignment with human reviewer concerns, especially for novelty-related issues.