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The libraries and presses of three major universities—The Chinese University of Hong Kong, City University of Hong Kong, and The University of Hong Kong—jointly launched Hong Kong's first open access book program. All books are licensed under CC BY-NC-ND 4.0, allowing free sharing but only for non-commercial use.
ArXiv discusses future developments and improvements to its preprint repository.
Review-it.ai helps PhD students find journals likely to accept their paper by uploading the manuscript.
Springer Nature has retracted two studies conducted by researchers at the Max Planck Institute, citing concerns over the validity of the findings.
Traxia introduces a framework for verifiable, agent-native scientific publishing where autonomous AI agents publish, peer-review, and collaborate with humans, addressing reproducibility and provenance issues.
This paper investigates the alignment of LLM-generated reviews with human judgment using 1k real ACL 2025 submissions, finding limited agreement, instability across models/prompts, and a method to artificially inflate scores without meaningful changes. The authors advise against relying solely on LLM reviews and call for discussion on their use in handling increasing submission volumes.
This paper introduces AiraXiv, an AI-driven open-access platform designed for both human and AI scientists, featuring interactive UI and MCP-based interactions to support continuous, feedback-driven paper iteration and scalable research infrastructure.
Almost the entire editorial board of the Journal of Approximation Theory resigned due to a dispute with the publisher.
ArXiv is implementing a new policy that bans authors for one year if submitted papers show clear evidence of unchecked AI generation, such as hallucinated references or LLM comments, reinforcing that authors are fully responsible for content regardless of how it was produced.
ArXiv, a popular preprint platform, will ban authors for one year if they submit papers containing clear signs of unchecked LLM-generated content, such as hallucinated references or LLM meta-comments, to reduce AI slop.
Author seeks advice on anonymizing GitHub repositories when submitting AI/ML papers to conferences.
A tier-3 college final-year ISE student with ongoing ML research publications (TMLR, NeurIPS targets) seeks advice on the practical value of research credentials for industry jobs in India and higher studies abroad, versus traditional DSA/dev focus.
A researcher discusses their ICML 2026 paper review experience where a reviewer increased their score during rebuttal but then decreased it again, expressing concern about rejection prospects.