Research5d ago
Scaling Interaction Analysis for LLMs
The BAIR blog presents a framework that scales interaction analysis to millions of LLMs parameters. It combines feature attribution, data attribution, and mechanistic interpretability to trace predictions back to training data and internal modules. By mapping these links, developers can pinpoint bias and failure modes. The approach offers a practical tool for safer, more transparent AI.