AINeutralarXiv – CS AI · 8h ago6/10
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DART: Draft-Agreement Routing for Training-Free Adaptive Thinking Budgets in Hybrid Reasoning Models
Researchers introduce DART, a training-free routing framework that dynamically allocates computational thinking budgets in hybrid reasoning models by sampling cheap draft responses and using agreement patterns to decide between direct answers and extended reasoning. The approach achieves significant accuracy improvements on math and code tasks while reducing token consumption by 15-69%, without requiring labeled data or model fine-tuning.