The BAIR blog outlines a framework that scales interaction analysis to millions of LLM tokens. It combines feature, data, and mechanistic attribution to isolate the inputs, training examples, and internal functions that drive predictions. Researchers cite Lundberg, Ribeiro, Koh, and Ilyas as foundational works guiding the method. Practitioners can use the approach to pinpoint model weaknesses and improve safety.