AIBullisharXiv – CS AI · Mar 176/10
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Mitigating Overthinking in Large Reasoning Language Models via Reasoning Path Deviation Monitoring
Researchers propose a new early-exit method for Large Reasoning Language Models that detects and prevents overthinking by monitoring high-entropy transition tokens that indicate deviation from correct reasoning paths. The method improves performance and efficiency compared to existing approaches without requiring additional training overhead or limiting inference throughput.