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Mechanistic and Attributional Interpretability in Neuroscience

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If you have a question about this talk, please contact Dr. Michail Mamalakis .

In this seminar, we will briefly discuss basic terminology in mechanistic interpretability, examine different sparse auto-encoder (SAEs) architectures and techniques beyond SAEs, and explore examples of LLMs applied in neuroscience, as well as how mechanistic interpretability and attribution methods can be combined to identify new patterns.

This talk is part of the Foundation AI series.

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FW 11, Willam Gates Hall. Zoom link: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon https://zoom.us/j/92924554238 FW11, William Gates Building. Zoom link: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon

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