TL;DR: adVersarial Parameter Decomposition (VPD) decomposes model weights into simple components and then labels each component as "needed here" or "safe to remove here" for each token of the input. These labels make up the "explanation" of that input. A core aspiration of VPD is that inputs' explanations can aggregate...
Overview When I began my attempt to replicate Anthropic's Towards Monosemanticity paper, I had high expectations for how interpretable the extracted features should be. If I judged a feature to be uninterpretable, I attributed this to either sub-optimal sparse autoencoder hyperparameters, a bug in my implementation, or possible shortcomings of...
Summary Contrast-Consistent Search (CCS) is a method for finding truthful directions within the activation spaces of large language models (LLMs) in an unsupervised way, introduced in Burns et al., 2022. However, all experiments in that study involve training datasets that are balanced with respect to the ground-truth labels of the...