TokenScope: Token-Level Explainability and Interpretability for Code-Oriented Tasks in Large Language Models

Researchers have introduced TokenScope, a new diagnostic tool designed to analyze token-level decision-making processes within large language models during code generation. By improving visibility into how these models formulate specific programming outputs, the framework aims to help developers better identify and debug errors in AI-assisted coding tasks.