Research
152d agoScaling Interpretability for LLMs
Researchers develop scalable methods to trace how Large Language Models make decisions, combining feature, data, and mechanistic analysis. By linking predictions to specific inputs and training examples, the work enhances transparency and trust across industries.
The Signal
These techniques promise safer AI worldwide, enabling developers to audit models and stakeholders to understand behavior without relying on opaque black boxes.