@inproceedings{09ec405754c647a58edc070cd47ba955,
title = "Global Prompt Cell: A Portable Control Module for Effective Prompt Tuning",
abstract = "As a novel approach to tuning pre-trained models, prompt tuning involves freezing the parameters in downstream tasks while inserting trainable embeddings into inputs in the first layer. However, previous methods have mainly focused on the initialization of prompt embeddings. The strategy of training and utilizing prompt embeddings in a reasonable way has become a limiting factor in the effectiveness of prompt tuning. To address this issue, we introduce the Global Prompt Cell (GPC), a portable control module for prompt tuning that selectively preserves prompt information across all encoder layers. Our experimental results demonstrate a 5.8\% improvement on SuperGLUE datasets compared to vanilla prompt tuning.",
author = "Chi Liu and Haochun Wang and Nuwa Xi and Sendong Zhao and Bing Qin",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023 ; Conference date: 12-10-2023 Through 15-10-2023",
year = "2023",
doi = "10.1007/978-3-031-44693-1\_51",
language = "英语",
isbn = "9783031446924",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "657--668",
editor = "Fei Liu and Nan Duan and Qingting Xu and Yu Hong",
booktitle = "Natural Language Processing and Chinese Computing - 12th National CCF Conference, NLPCC 2023, Proceedings",
address = "德国",
}