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OV 'Concept Lenses' are said to give much better readouts in a vision-language model than a logit lens
A user credits Sheridan Feucht with pioneering a technique that summarizes attention-head-bundle OV transforms. The user says it gave much better readouts than a logit lens in a vision-language model.
TLDR
A user says Sheridan Feucht found OV 'Concept Lenses' while studying how language models copy text verbatim versus approximately. The user says the technique produced much better readouts than a logit lens in a vision-language model, and suggests Feucht's earlier findings point to a layered semantic structure in transformer language models.
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