Anytime Safe PAC Efficient Reasoning
📰 ArXiv cs.AI
arXiv:2601.22446v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have demonstrated remarkable performance on complex tasks but suffer from high computational costs and latency. While selective thinking strategies improve efficiency by routing easy queries to non-thinking models, existing approaches often incur uncontrollable errors, especially in online settings where the performance loss of a non-thinking model is only partially observed and data are non-stationary. To address
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