Paper Wins Runner-Up and Oral at ICML Workshop
StanfordAILab · x · 2026-07-10
The Stanford AI Lab reshared a paper that won runner-up at the ICML 2026 "Foundations of Deep Generative Models" workshop, titled "Internal Data Repetition Destroys Language Models".
The post confirms the work was selected for an oral presentation and lists the authors along with the presentation time and venue, marking a concrete progression in academic research and conferences.
Related event: Paper on Data Repetition Destroying LMs Wins ICML Workshop Oral(2 posts)→
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