Papers by Elena Golimblevskaia

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Challenge:	Recent advances in mechanistic interpretability have highlighted the potential of automating interpretability pipelines in analyzing the latent representations within LLMs.
Approach:	They propose a framework for automatically evaluating feature-to-description alignment that measures alignment across four key metrics and quantifies the causes of misalignment.
Outcome:	The proposed framework evaluates alignment across four key metrics and quantifies the causes of misalignment between features and descriptions.