Explainability
Concept Identification
Identifies learned concepts in models (e.g., CAVs, Neuron Activation Analysis)
3 techniques in this subcategory
3 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| Neuron Activation Analysis | Algorithmic | Architecture/neural Networks Requirements/model Internals +1 | Text | Neuron activation analysis examines when individual neurons in a neural network respond strongly. The analyst runs a set... | ||
| Concept Activation Vectors | Algorithmic | Architecture/neural Networks Requirements/gradient Access +2 | Any | A concept activation vector (CAV) is a direction inside a neural network that stands for a human idea such as 'stripes'.... | ||
| Sparse Autoencoder Feature Analysis | Algorithmic | Architecture/neural Networks/transformer Architecture/neural Networks/transformer/llm +2 | Text | Sparse autoencoder feature analysis looks for human-interpretable units inside a neural network, usually a language... |
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