Notation Matters: A Benchmark Study of Token-Optimized Formats in Agentic AI Systems 事件

Notation Matters: A Benchmark Study of Token-Optimized Formats in Agentic AI Systems arXiv:2605.29676v1 Announce Type: cross Abstract: Large language models in Agentic AI systems consume tool schemas and execution results and emit tool invocations as structured data. The default language for that exchange, JSON, was designed for application-to-application interchange rather than token efficiency, so its structural elements impose substantial token overhead. Recent work proposes token-optimized