Research9h ago
Scaling Interaction Identification for LLM Interpretability
Researchers at BAIR developed a method to identify interactions within large language models at scale. This approach moves beyond simple feature attribution to map how internal components collaborate. By dissecting these complex functions, the team provides a clearer path toward mechanistic interpretability. This allows developers to pinpoint exactly why specific model decisions occur.