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2026
Semantic Optimal Transport for Sparse Autoencoder Feature Matching and Circuit Compression
The paper introduces a distributional framework using Wasserstein distance to unify the semantic comparison of sparse autoencoder features across different layers and to automatically compress large feature circuits into interpretable supernodes.
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