Research3h ago
Scaling Interaction Identification in LLMs
Researchers at BAIR are developing methods to identify interactions at scale within Large Language Models. The approach integrates feature attribution, data attribution, and mechanistic interpretability to decode complex decision-making processes. This framework helps model builders isolate specific input features and training examples. It provides a technical path toward more transparent and safer AI system audits.