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charlieoneill
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embedding-saes

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sparse-autoencoder
embeddings
interpretability
scientific-nlp
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@@ -58,7 +58,7 @@ The SAEs were trained using a custom loss function combining reconstruction loss
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  Performance metrics for various configurations:
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- | k | n | Domain | MSE | Log FD | Act Mean |
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  |-----|-------|----------|--------|---------|----------|
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  | 16 | 3072 | astro.PH | 0.2264 | -2.7204 | 0.1264 |
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  | 16 | 3072 | cs.LG | 0.2284 | -2.7314 | 0.1332 |
 
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  Performance metrics for various configurations:
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+ |k |n |Domain |MSE |Log FD |Act Mean |
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  |-----|-------|----------|--------|---------|----------|
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  | 16 | 3072 | astro.PH | 0.2264 | -2.7204 | 0.1264 |
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  | 16 | 3072 | cs.LG | 0.2284 | -2.7314 | 0.1332 |