AIBullisharXiv – CS AI · Jun 56/10
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Learning Adaptive Parallel Execution for Efficient Code Localization
Researchers introduce FuseSearch, an AI system that optimizes parallel code localization by reducing redundant tool invocations from 34.9% to near-zero through adaptive execution strategies. The approach combines supervised fine-tuning and reinforcement learning to dynamically adjust search breadth, achieving state-of-the-art performance on SWE-bench while using 68.9% fewer tokens and delivering 93.6% speedup.
