arXiv:2606. 01013v1 Announce Type: new Abstract: Research is advancing faster than ever with artificial intelligence (AI); and so are the corresponding research papers.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
arXiv:2605. 03202v2 Announce Type: replace Abstract: Large language models offer a tempting solution to address the peer review crisis.
arXiv:2606. 10159v1 Announce Type: cross Abstract: AI is increasingly used to support scientific peer review, from manuscript screening, reviewer assistance to editorial triage.
arXiv:2506. 08134v4 Announce Type: replace Abstract: Peer review, the bedrock of scientific advancement in machine learning (ML), is strained by a crisis of scale.
PaperDoctor is an agent framework that provides evidence‑grounded, actionable feedback for scientific papers before submission. It evaluates writing, layout, references, code, theory, prior work, and experiments through a three‑layer hierarchical system, linking each critique to specific evidence and revision suggestions. The system selectively rebuilds and reruns experiments to uncover reproducibility gaps, and an interactive interface lets authors explore findings tied to their manuscript.
arXiv:2608. 14625v1 Announce Type: cross Abstract: Academic peer review is under mounting strain: NeurIPS 2025 received 21,575 submissions, ICLR 2025 received 11,603, and ICML 2025 received 12,107.
AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publication venues regulate its use or of how capable current AI review systems are. We address these questions by first surveying reviewer-facing AI policies across 111 leading AI/NLP conferences and medical journals, revealing substantial regulation differences between the two communities.