Toward Tool-Augmented Semantic Computing: Integrating Large Language Models with Data Grounding and Optimization for Real-World Problem Solving
This paper proposes a framework for tool-augmented semantic computing, in which LLMs are combined with external data sources and specialized algorithmic components, and demonstrates how tasks such as point-of-interest selection, coordinate retrieval, and route optimization can be decomposed into modular processing step...