AINeutralarXiv – CS AI · 10h ago6/10
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EGL-SCA: Structural Credit Assignment for Co-Evolving Instructions and Tools in Graph Reasoning Agents
Researchers introduce EGL-SCA, a framework for graph reasoning agents that jointly optimizes both natural language instructions and computational tools through structural credit assignment. The system achieves 92.0% success rate on graph reasoning benchmarks by precisely routing failures to either prompt optimization or tool synthesis, outperforming isolated improvement approaches.