New paper dissects only task-relevant network parts, making mechanisms inspectable and editable at far lower cost
leedsharkey · x · 2026-10-02
A new interpretability paper proposes dissecting only the parts of a neural network actually used for a task of interest, instead of decomposing the whole network. This is much cheaper and yields mechanisms that can be inspected, erased, or edited to change model behavior. A detailed thread expands on the method.
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