What models represent internally, how that information is organized, and how it affects their behavior.
What models represent internally, how that information is organized, and how it affects their behavior.
What models internally encode and how they use it: attention analysis, layer-wise probing, sparse autoencoders, and mechanistic explanations. Generalization tests remain under evidence/generalization.
29 items with this tag.
How similarities, clusters, distances, and manifolds in model representations relate to sequence, structure, or function. Practical feature extraction is a separate inference topic.
14 items with this tag.