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News/Cross-seed explainability using Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoders
arxiv
PublishedJuly 11, 2026 at 4:00 AM
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Cross-seed explainability using Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoders

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arXiv:2607.08499v1 Announce Type: new Abstract: We present a Procrustes-conditioned Joint End-to-end Top-K Sparse Autoencoder (SAE) for extracting cross-seed universal features from independently trained BERT models. Cross-seed feature universality is a fundamental challenge in mechanistic interpret

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