Cross-Context Review: Improving LLM Output Quality by Separating Production and Review Sessions
Large language models often approve their own flawed work because they review outputs in the same session that created them. This study introduces Cross-Context Review (CCR), which separates generation from verification. By forcing reviewers to check artifacts in a completely new session with no production history, CCR significantly improves output quality across different artifact types.