The described method computes attribution to a sparse autoencoder by taking the dot product of the gradient with the autoencoder's decoder.

“um and what you can do is this means you can also do attribution to the SAE so during a backward pass um you can take the gradients and they're just flowing backwards through the model at some point there'll be the gradients with respect to the residual stream at the SAE layer”

“And then you get like attribution to the SAE by just taking the dot product of the gradient against the decoder of the auto encoder.”