Mechanistic Interpretability Researchers Apply Causality Theory to LLMs

Researchers are using causal inference methods to understand how large language models reason internally. This approach bridges mechanistic interpretability and causality theory, offering new techniques to trace decision pathways and identify which model components drive specific outputs.

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