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adamkarvonen/saebench_pythia-160m-deduped_width-2pow14_date-0108

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SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability

This repository contains models described in the paper SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability. SAEBench is a comprehensive evaluation suite that measures SAE performance across seven diverse metrics, spanning interpretability, feature disentanglement and practical applications like unlearning.