1 link tagged with all of: language-models + steering + attribution + latent-features + misalignment
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This article explores how sparse-autoencoder latent attribution can identify the causes of misalignment in language models. It presents two case studies demonstrating how specific latent features can steer models toward undesirable behaviors, revealing a strong link between provocative content and misalignment.
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