A fine-grained self-adapting prompt learning approach for few-shot learning with pre-trained language models

已完结 10 由 xhuis 发布于 2026/8/2 9:47:35

DOI:10.1016/j.knosys.2024.111968
作者：Xiaojun Chen ,?Ting Liu ,?Philippe Fournier-Viger ,?Bowen Zhang ,?Guodong Long ,?Qin Zhang
文献类型：期刊论文
补充材料：只需要正文

Elsevier

Abstract：Pre-trained language models have demonstrated remarkable performance in few-shot learning through the emergence of “prompt-based learning” methods, where the performance of these tasks highl

应助信息

19小时前

一羊万洗

e09a39148e1411f1862534735aa3bc31.pdf 已采纳

19小时前

Book学术机器人

2026/8/2 9:47:35 未找到该文献，机器人已退出，请等待人工下载

2026/8/2 9:47:35 Book学术AI机器人收到请求，开始寻找文献

2026/8/2 9:47:35 已向机器人发送请求

19小时前

xhuis 发布求助

上一个求助:其它数据库Naturally Fractured Carbonate Reservoir Characterization: A Case Study of a Mature High-Pour Point Oil Field in Hungary 下一个求助:知网融合对抗解耦与特征对齐的野生动物图像开集域适应方法