Frozen Weights as Prior for Parameter-Efficient Fine-Tuning

Frozen Weights as Prior for Parameter-Efficient Fine-Tuning

In the fields of natural language processing and computer vision, the emergence of large pre-trained models has led to the adoption of fine-tuning them for downstream tasks as an important paradigm. However, the full fine-tuning approach often comes with a hefty cost, which is not feasible for many...

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Bibliographic Details
Main Authors: Xiaolong Ma, Peishun Liu, Haojie Gao, Zikang Yan, Ningning Ma, Wenqiang Liu, Xuefang Wang, Ruichun Tang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Fine-tuning
PEFT
large pre-trained models
transfer learning
adaptation
Online Access:https://ieeexplore.ieee.org/document/10840174/
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