"Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs" arxiv.org/abs/2402.03927
Who's Who of AI
YY Ahn
Prof @ School of Data Science, University of Virginia. Formerly at IU. Networks, data science, and machine learning. https://yyahn.com
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Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs arxiv.org
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This paper looks cool: arxiv.org/abs/2605.23901 "We propose the Shannon Scaling Law, a unified theoretical framework that models LLM training as information transmission over a noisy channel ... The Shannon Scaling Law consistently outperforms classical scaling laws ..."
Sutton's "Bitter Lesson" keeps showing up in new corners. Latest example on data filtering for pretraining: arxiv.org/abs/2605.19407 "... with enough compute, the best data filter is no data filter." -- Btw, Welch Labs has a nice video on the "bitter lesson": www.youtube.com/w…
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