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So, to summarize: >Used "dictionary learning" >Found abstract features >Found similar/close features using distance >Tried amplifying and suppressing featur
by pdevr 2y ago
So, to summarize:
>Used "dictionary learning"
>Found abstract features
>Found similar/close features using distance
>Tried amplifying and suppressing features
Not trying to be snary, but sounds mundane in the ML/LLM world. Then again, significant advances have come from simple concepts. Would love to hear from someone who has been able to try this out.
- sjkoelle 2y agothe interesting advance in the anthropic/mats research program is the application of dictionary learning to the "superpositioned" latent representations of transformers to find more "interpretable" features. however, "interpretability" is generally scored by the explainer/interpreter paradigm which is a bit ad hoc, and true automated circuit discovery (rather than simple concept representation) is still a bit off afaik.