AIBullisharXiv – CS AI · May 97/10
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ReaComp: Compiling LLM Reasoning into Symbolic Solvers for Efficient Program Synthesis
ReaComp introduces a method to compile reasoning traces from large language models into reusable symbolic program synthesizers that eliminate runtime LLM calls. The approach achieves 91.3% accuracy on benchmark tasks while reducing token usage by 78%, demonstrating that neuro-symbolic hybrid systems can outperform pure LLM inference on complex program synthesis problems.