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LLMs are rapidly transforming peer review, but critical gaps remain in ensuring quality, fairness, and ethical considerations across the entire workflow.
Training on SciMDR, a new 300K QA dataset synthesized from scientific papers, substantially boosts model performance on complex, document-level scientific reasoning tasks.
Stop generating superficial reviews: RbtAct leverages rebuttals to train LLMs to provide actionable feedback, leading to concrete revisions and improved author uptake.
Even GPT-5 struggles to reliably reproduce novel research findings, highlighting a significant gap between capability and reliability for AI agents tackling end-to-end research tasks.
