EleutherAI has introduced Product Key Memory (PKM) sparse coders as an alternative to TopK sparse coders, aiming to improve reconstruction accuracy in language models. Their research indicates that PKM coders can train faster and offer slightly better interpretability, although baseline models may perform better at very large sizes. The team has released code and trained models for PKM coders, which decompose large MLP input projections to potentially reduce computational costs. AI
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RANK_REASON This is a research paper detailing a new technique for sparse coders in language models, including code and model releases.
