AI reviews for all 22,977 AAAI-26 papers were preferred by authors and PC members over human reviews on accuracy and suggestions and outperformed baselines at spotting weaknesses.
Russo Latona, M
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Fine-tuned LLMs trained on social science publication records outperform experts and frontier models at judging which research pitches deserve attention.
Authors show prompt injection attacks that jailbreak LLM paper reviewers for biased acceptance and propose embedding triggers to detect when reviews are LLM-generated rather than human.
PeerCheck finds that chain-of-thought prompting improves LLM academic reviews while retrieval-augmented generation sometimes lowers quality, and that LLMs and humans emphasize different aspects of papers.
Introduces the Agentic Publication Protocol (APP) as a repository-based standard for publishing papers together with reproducibility artifacts and agent instructions.
SafeReview trains a Generator to create adversarial prompts and a Defender to detect them via co-evolution with an IR-GAN-inspired loss, claiming better resilience than static defenses for LLM-based peer review.
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 survey synthesizing LLM methods for peer review critique generation and score prediction, including taxonomies, benchmark limitations, domain biases, and robustness risks such as prompt injection.
AI can generate research artifacts faster than it can verify them, so across all eight lifecycle stages the credible deployment mode is human-governed collaboration rather than full autonomy.
citing papers explorer
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AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot
AI reviews for all 22,977 AAAI-26 papers were preferred by authors and PC members over human reviews on accuracy and suggestions and outperformed baselines at spotting weaknesses.
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LLMs learn scientific taste from institutional traces across the social sciences
Fine-tuned LLMs trained on social science publication records outperform experts and frontier models at judging which research pitches deserve attention.
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ChatGPT: Excellent Paper! Accept It. Editor: Imposter Found! Review Rejected
Authors show prompt injection attacks that jailbreak LLM paper reviewers for biased acceptance and propose embedding triggers to detect when reviews are LLM-generated rather than human.
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PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality
PeerCheck finds that chain-of-thought prompting improves LLM academic reviews while retrieval-augmented generation sometimes lowers quality, and that LLMs and humans emphasize different aspects of papers.
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Agentic Publication Protocol: An Attempt to Modernize Scientific Publication
Introduces the Agentic Publication Protocol (APP) as a repository-based standard for publishing papers together with reproducibility artifacts and agent instructions.
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SafeReview: Defending LLM-based Review Systems Against Adversarial Hidden Prompts
SafeReview trains a Generator to create adversarial prompts and a Defender to detect them via co-evolution with an IR-GAN-inspired loss, claiming better resilience than static defenses for LLM-based peer review.
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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
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.
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LLM-Based Scientific Peer Review: Methods, Benchmarks, and Reliability Challenges
A survey synthesizing LLM methods for peer review critique generation and score prediction, including taxonomies, benchmark limitations, domain biases, and robustness risks such as prompt injection.
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AI for Auto-Research: Roadmap & User Guide
AI can generate research artifacts faster than it can verify them, so across all eight lifecycle stages the credible deployment mode is human-governed collaboration rather than full autonomy.
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