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computers and graphics (pergamon)(1)

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作者

Xing J. AND Liu J. AND Wang J. AND Sun L. AND Chen X. AND Gu X. AND Wang Y.(0)

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agricultural information institute, chinese academy of agricultural sciences, beijing, 100081, china(1)
college of computer science and engineering, north minzu university, yinchuan, 750021, china(1)
college of computer science and engineering, north minzu university, yinchuan, 750021, china, the key laboratory of images and graphics intelligent processing of state ethnic affairs commission, north minzu university, yinchuan, 750021, china(1)

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2024(1)

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资源类型: 外文期刊

作者:Xing J.(精确检索)

作者:Liu J.(精确检索)

作者:Wang J.(精确检索)

作者:Sun L.(精确检索)

作者:Chen X.(精确检索)

作者:Gu X.(精确检索)

作者:Wang Y.(精确检索)

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1A survey of efficient fine-tuning methods for Vision-Language Models — Prompt and Adapter

作者： Xing J.; Liu J.; Wang J.; Sun L.; Chen X.; Gu X.; Wang Y.; SCIE（2024版） EI（2024版）

机构： College of Computer Science and Engineering, North Minzu University, Yinchuan, 750021, China; College of Computer Science and Engineering, North Minzu University, Yinchuan, 750021, China, The Key Laboratory of Images and Graphics Intelligent Processing of State Ethnic Affairs Commission, North Minzu University, Yinchuan, 750021, China; Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China;

来源：Computers and Graphics (Pergamon)

关键词： Adapter Computer vision Efficient fine-tuning Pre-training model Prompt Vision-language