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Token-Oriented Object Notation and JSON data format comparison in terms of token size , context window, token cost money, llm readability and data readability along with retrieval of context by the LLMs.
This project aims to research and construct a method for evaluating the coverage of a systematic multi-agent system (MAS) test, and to establish a test evaluation index system suitable for different application scenarios.
Five chapters on testing model output without a research budget: choosing criteria, building an eval set with known good answers, picking script versus model versus human judges, and catching regressions.