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Interpretable AI: Attention Maps, Sparse Autoencoders, and Steering Vectors Explained with Code
Three hands-on interpretability techniques for understanding what language models think: attention visualization with circuitsvis, sparse autoencoders for hidden concept discovery, and steering vectors for behavior control—all with runnable code.
March 14, 2026
20 min read
#Interpretability#Explainable AI#Attention Maps#Sparse Autoencoders#Steering Vectors#PyTorch#Transformers#LLM