Cut Fine-Tuning Cost: Adapt LMs to Multi-Modal Tasks with <1% New Params
文章探讨了模型调优技术在主动学习中的应用，提出了一种名为UNIPELT的框架，结合BitFit、Adapter和Prefix-Tuning等方法，并通过门控机制提升模型的稳定性和适应性，在多任务和多模态场景中表现出色。 2025-9-9 08:54:16 Author: hackernoon.com(查看原文) 阅读量:3 收藏

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Transferring the essence of optimal performance, and saving the model from the abyss of underfitting.

September 9th, 2025

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    Transferring the essence of optimal performance, and saving the model from the abyss of underfitting.

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Transferring the essence of optimal performance, and saving the model from the abyss of underfitting.

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