Many users congratulated the Stanford team on their ICML workshop runner-up win for showing how internal data repetition destroys language models, praising the research finding.
Based on 3 visible X reactions from 4 accounts; directional sample.
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@SithyPoo Thank you!
@RylanSchaeffer Congrats!
@jchudnov 👏👏
Internal Data Repetition Destroys Language Models" was selected as an Oral & Best Paper Runner Up at #ICML2026 's Workshop Foundations of Deep Generative Models 🥳🥳🥳 Slides are here! https://docs.google.com/presentation/d/1x0AHfZpgB8pQDbX4bEwcYKl5bswq5HQpFgjoCQgFOP4/edit?slide=id.p#slide=id.p https://twitter.com/jchudnov/status/2075358259138236597
The researchers analyzed the degradation using a 344M parameter model.
Many users congratulated the Stanford team on their ICML workshop runner-up win for showing how internal data repetition destroys language models, praising the research finding.
Based on 3 visible X reactions from 4 accounts; directional sample.
Ask a question below.
Published answers will appear here.