Research1d ago
Scaling Interaction Identification in LLMs
Researchers at BAIR are developing methods to identify interactions at scale within large language models. The work bridges feature attribution and mechanistic interpretability to uncover how internal components drive specific predictions. This approach helps model builders map complex decision-making processes. It provides a more transparent framework for auditing model behavior.