EP256: Teaching AI to Doubt Its Own Answers

Title: Confidence-Orchestrated Self-Evolution against Uncertain LLM FeedbackSource: http://arxiv.org/abs/2605.28010v1Summary:COSE provides a foundational framework for LLM self-evolution by using intrinsic model confidence as an uncertainty signal to filter and weigh self-generated training signals. This approach addresses the critical bottleneck of error propagation in autonomous learning loops, enabling models to improve their reasoning and mathematical capabilities without human-curated supervision or external verifiers.