Prefix Tuning Using Residual Reparameterization
Fine-tuning large language models for specific tasks requires updating and storing all parameters, leading to significant computational and storage cost issues. To address these challenges, parameter-efficient learning such as prefix tuning has gained attention. However, prefix tuning can suffer fro...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10938609/ |
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