Semantic role understanding partially emerges during language model pre-training, with linear probes on frozen representations achieving substantial performance that improves with scale but does not match fine-tuned models, and representations shifting toward more distributed forms at larger scales.
Interpretability in the Wild: A Circuit for Indirect Object Identification in
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A grid-free attention-based deep learning model interpolates surface-level PM2.5 concentrations across the US using sparse sensor data and auxiliary geospatial features.
citing papers explorer
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Emergent Semantic Role Understanding in Language Models
Semantic role understanding partially emerges during language model pre-training, with linear probes on frozen representations achieving substantial performance that improves with scale but does not match fine-tuned models, and representations shifting toward more distributed forms at larger scales.
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Mechanistic Anomaly Detection via Functional Attribution
A grid-free attention-based deep learning model interpolates surface-level PM2.5 concentrations across the US using sparse sensor data and auxiliary geospatial features.