Catherine Arnett

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Researcher with public evidence across NLP & language, AI research.

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NLP Researcher at EleutherAI, PhD UC San Diego Linguistics. Interested in multilingual NLP, tokenizers, open science. 📍Boston. She/her. https://catherinearnett.github.io/

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Catherine Arnett reposted
James Michaelov @jamichaelov.bsky.social

Seems like a good time to share our new preprint about model openness! (with @catherinearnett.bsky.social @tylerachang.bsky.social Pamela D. Rivière, Samuel M. Taylor @camrobjones.bsky.social @seantrott.bsky.social @rplevy.bsky.social Ben Bergen, and Micah Altman): arxiv.org/a…

How Open Must Language Models be to Enable Reliable Scientific Inference? arxiv.org
AI Weekly's analysis
  • Closed model performance can vary by up to 60% across undocumented version updates, making past benchmark results irreproducible.
  • The paper defines open-weight models as providing complete weights, tokenizer, full architecture, and sufficient code to run independently.
  • Authors recommend researchers justify model selection and systematically document threats to inference when using LLMs in research.
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