1% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions-Reference-Cited by-同舟云学术

1% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions

Published:2023-06 Issue: Volume: Page:
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Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Yin Dongshuo¹,Yang Yiran¹,Wang Zhechao¹,Yu Hongfeng¹,Wei Kaiwen¹,Sun Xian¹

Affiliation:

1. Key Laboratory of Network Information System Technology, Aerospace Information Research Institute, Chinese Academy of Sciences

Publisher

IEEE

Link

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2. IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

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