计算机科学与探索2024，Vol.18Issue(9)：2293-2325,33.DOI:10.3778/j.issn.1673-9418.2402023
AIGC大模型测评综述:使能技术、安全隐患和应对
Survey of AIGC Large Model Evaluation:Enabling Technologies,Vulnerabilities and Mitigation
摘要
Abstract
Artificial intelligence generated content(AIGC)models have attracted widespread attention and applica-tion worldwide due to their excellent content generation capabilities.However,the rapid development of AIGC large models also brings a series of hidden dangers,such as concerns about interpretability,fairness,security,and privacy preservation of model-generated content.In order to reduce the unknowable risks and their harms,it be-comes more and more important to carry out a comprehensive measurement and evaluation of AIGC large models.Academics have initiated AIGC large model evaluation studies aiming to effectively address the related challenges and avoid potential risks.This paper summarizes and analyzes the AIGC large model evaluation studies.Firstly,an overview of the model evaluation process is provided,covering model evaluation pre-preparation and corresponding measurement indicators,and existing measurement benchmarks are systematically organized.Secondly,the repre-sentative applications of the AIGC large model in finance,politics and healthcare and their problems are discussed.Then,the measurement methods are studied in depth through different perspectives,such as interpretability,fair-ness,robustness,security and privacy,and the new issues that need to be paid attention to AIGC large model evaluation are deconstructed,and the ways to cope with the new challenges of large model evaluation are pro-posed.Finally,the future challenges of AIGC large model evaluation are discussed,and its future development direc-tion is envisioned.关键词
AIGC大模型/大模型测评/可解释性/公平性/鲁棒性/安全与隐私保护Key words
AIGC large model/large model evaluation/interpretability/fairness/robustness/security and privacy protection分类
信息技术与安全科学引用本文复制引用
许志伟,李海龙,李博,李涛,王嘉泰,谢学说,董泽辉..AIGC大模型测评综述:使能技术、安全隐患和应对[J].计算机科学与探索,2024,18(9):2293-2325,33.基金项目
国家自然科学基金地区项目(61962045,62272248) （61962045,62272248）
内蒙古青年科技英才支持项目(NJYT23104). This work was supported by the National Natural Science Foundation of China(61962045,62272248),and the Inner Mongolia Support Plan for Young Science and Technology Talents(NJYT23104). （NJYT23104）
