Tung-Yu Wu
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Understanding AI from the Inside: The State of Mechanistic Interpretability for AI Safety
According to the abstract, Barez and 26 co-authors survey mechanistic interpretability and ask whether understanding how models work makes them safer. They propose a framework for evaluating interpretability claims, discuss limits, and release code notebooks.