A survey of mechanistic interpretability concepts, methods, benefits for AI safety, risks, and scalability challenges in understanding neural network computations.
Going beyond neural network feature similarity: The network feature complexity and its interpretation using category theory.CoRR, November 2023a
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Mechanistic Interpretability for AI Safety -- A Review
A survey of mechanistic interpretability concepts, methods, benefits for AI safety, risks, and scalability challenges in understanding neural network computations.