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A satirical guest post on Terence Tao's blog by physicist Rikab Gambhir criticizing OpenAI's release of 722 AI-generated math manuscripts, arguing that mass-generating plausible-looking but unverified papers outsolds the burden of verification onto the mathematics community.
Google Research publicly released Deep Review, an agentic AI system for rigorous technical document review across academic, legal, and finance domains, evolving from its Paper Assistant Tool pilots with major CS conferences. It offers tiered access with a scalable Gemini API and guarantees uploaded documents are not used for model training.
Sakana AI researchers introduce a verification-centric benchmark for LLM-assisted peer review, built on synthetic error insertion into conference papers, and a Multi-Layered Review (MLR) framework that improves error detection, human alignment, and token efficiency while exposing remaining adversarial vulnerabilities.
一篇关于学术出版界遭 AI 生成论文污染的报道，探讨了「vegetative electron microscopy」这一由 OCR 错误产生、却被大量论文照抄的指纹短语，暴露了论文工厂与出版商审查失职的问题。
An opinion piece arguing that AI-discovered proofs of long-standing open math problems should be published promptly, and that mathematicians are not entitled to special protection from AI-driven discovery beyond proper verification and attribution. The author, a creative professional, contends technological displacement already hit creative fields and that slowing scientific progress for a profession's adjustment period is unjustified.
The paper introduces PASS, an agentic AI system that predicts publication venues for manuscripts by analyzing literature context, achieving high accuracy and outperforming baselines, and is released as a public platform for researchers.
Datalab is releasing a new processor that converts PDFs to JATS XML, reducing cost to cents per page and time to under 5 minutes with 92.6% accuracy in a human-matched benchmark.
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.
A Twitter thread analyzes the unusually long peer review process for a cell embedding paper using GPT-5.6 to compare the preprint and final publication, estimating time, compute, personnel, and APC costs, highlighting the cost-benefit ratio of journal peer review.
Science historians discover that the journal Naturwissenschaften retracted two 1940s papers by Max Planck, likely due to a copyright-related algorithm error, leading to blank pages and empty PDFs.
A new study demonstrates that AI-assisted peer review is vulnerable to low-cost manipulation via superficial rephrasing of paper abstracts, significantly inflating AI-generated review scores and potentially biasing human editorial decisions, highlighting the need for safeguards.
Tim O'Reilly discusses the challenges of integrating AI into scientific publishing, including hallucinated citations, propagation of retracted papers, and training on compromised literature, and calls for adapting existing scientific infrastructure for AI use.