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Social reasoning in language models is rooted in distinct training data, with targeted unlearning revealing its vulnerability to data removal.
Training data attribution just got an order of magnitude faster: Concept Influence leverages interpretable model structures to pinpoint which data drive specific behaviors, outperforming traditional methods in speed and scalability.