Researchers at BAIR developed a method to identify interactions between model components at scale. This approach moves beyond simple feature attribution to dissect internal functions. It provides a more transparent view of how LLMs reach specific decisions. Practitioners can now better isolate the exact training examples or internal weights driving problematic model behaviors.