A comprehensive effectiveness evaluation framework for domain-specific models
Song Yuan1，Zhang Kan1，2，Ren Yihui1，Huang Xiaopeng1
1. Suzhou Artificial Intelligence Co., Ltd.; 2. Suzhou International Development Group Co., Ltd.
Abstract： This paper addresses the issues of single evaluation dimensions, lack of domain adaptability, and fragmented methods in the evaluation practice of domain-specific models, and proposes a comprehensive effectiveness evaluation framework. This study aims to address the "evaluation gap" between technology research and development and industrial application through standardized solutions, providing a scientific basis for the development, deployment, and supervision of domain-specific models. The research method includes constructing a multidimensional indicator system centered on security compliance, technical performance, and application value, and designing a supporting evaluation dataset construction strategy and a hybrid evaluation method. The latter integrates automated testing, manual evaluation, and large models as evaluation means. The research results form a structured evaluation system that covers the classification of evaluation objects, indicator definition, and method implementation, which can achieve a comprehensive and comparable evaluation of different types of domain-specific models. The conclusion shows that the framework helps to improve the objectivity and operability of the evaluation and promote the trustworthy application of domain-specific models in key areas. In the future, it will need to be verified in practice and dynamically optimized to adapt to technological development.
Key words : artificial intelligence; domainspecific model; model evaluation
