Reviewer slates that are topically diverse, seniority-diverse, or from distinct publication networks produce broader or less redundant reviews, while geographic and organizational diversity show little or no effect.
Can we automate scientific reviewing? Journal of Artificial Intelligence Research, 75:171–212
8 Pith papers cite this work, alongside 73 external citations. Polarity classification is still indexing.
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Through 27 interviews and a design probe, the study shows area chairs differ substantially in engagement style and are cautiously open to AI assistance that adapts to their workflows.
A simple title-and-abstract model predicts citation counts better than review scores and outperforms LLM reviewers in matching human review scores, but remains below human consistency.
Peer review reports in AI conferences have grown longer and more standardized after LLMs, with increased emphasis on surface-level clarity and summaries at the expense of deeper critiques on originality and replicability.
A systematic review of LLM-based systems for hypothesis discovery, experiment planning, scientific writing, and peer review, including benchmarks, evaluation methods, and open challenges.
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A persistent, structured prompt loaded into an LLM chat session can guide reasoning models through critical analysis of experimental chemistry papers, but the evidence is a single qualitative case study.
A survey of LLM-based automated scholarly paper review, cataloging models, datasets, methods, and publisher policies as of 2023-2024.
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Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI
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