← heapsort-ai

research integrity

7 items

ARTICLE↑ trendingReddit r/MachineLearning·5/6/2026

Stop letting LLMs edit your .bib [D]

The author expresses shock at the frequent hallucinated citations by LLMs in academic papers, leading to incorrect author lists. They question the lack of respect for research and the need for harsher penalties, asking if others are experiencing the same issue.

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CASE↑ trendingReddit r/MachineLearning·4/8/2026

[D] Dealing with an unprofessional reviewer using fake references and personal attacks in ICML26

Um autor descreve enfrentar um avaliador extremamente antiprofissional no ICML 2026, que utilizou referências falsas, ataques pessoais e argumentos sem sentido para desqualificar seu trabalho. O autor busca orientação sobre como intervir contra um avaliador que emprega citações fraudulentas e ataques ad hominem no processo de revisão por pares.

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RESEARCHarXiv CS.AI·5/6/2026

Stop Automating Peer Review Without Rigorous Evaluation

This paper argues against using current AI systems for peer review, identifying two critical issues: a "hivemind effect" that reduces perspective diversity and the trivial gameability of AI review scores through paper rewriting. Empirical comparison of human- versus AI-generated reviews shows that AI reviewers are susceptible to stylistic changes rather than scientific merit, highlighting the need for non-gameability and review diversity for automation.

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