GeoSAE extracts a compact, interpretable feature set from frozen brain MRI foundation models that predicts MCI-to-AD conversion (AUC 0.746) with age-deconfounded annotations and replicates across cohorts.
Inter- preting and steering protein language models through sparse autoencoders
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
ESM2-8M predicts N-terminal methionine via retrieval from a positional prior at the beginning-of-sequence token through distributed attention circuits rather than direct biological detection.
citing papers explorer
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GeoSAE: Geometric Prior-Guided Layer-Wise Sparse Autoencoder Annotation of Brain MRI Foundation Models
GeoSAE extracts a compact, interpretable feature set from frozen brain MRI foundation models that predicts MCI-to-AD conversion (AUC 0.746) with age-deconfounded annotations and replicates across cohorts.
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Retrieval and competition: how a protein foundation model starts a protein
ESM2-8M predicts N-terminal methionine via retrieval from a positional prior at the beginning-of-sequence token through distributed attention circuits rather than direct biological detection.