Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models

In three linesPUMA detects semantic redundancy in reasoning chains to halt inference in large reasoning models before wasting tokens. The framework combines a lightweight redundancy detector with answer-level verification, achieving 26.2% average token reduction across five benchmarks while preserving accuracy and reasoning coherence.

Summary generated by Claude — human-verified