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%0 Conference Proceedings
%T ADEPT: Adapter-based Efficient Prompt Tuning Approach for Language Models
%A Shah, Aditya
%A Thapa, Surendrabikram
%A Jain, Aneesh
%A Huang, Lifu
%Y Sadat Moosavi, Nafise
%Y Gurevych, Iryna
%Y Hou, Yufang
%Y Kim, Gyuwan
%Y Kim, Young Jin
%Y Schuster, Tal
%Y Agrawal, Ameeta
%S Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada (Hybrid)
%F shah-etal-2023-adept
%R 10.18653/v1/2023.sustainlp-1.8
%U https://aclanthology.org/2023.sustainlp-1.8
%U https://doi.org/10.18653/v1/2023.sustainlp-1.8
%P 121-128

Markdown (Informal)

[ADEPT: Adapter-based Efficient Prompt Tuning Approach for Language Models](https://aclanthology.org/2023.sustainlp-1.8) (Shah et al., sustainlp 2023)

• ADEPT: Adapter-based Efficient Prompt Tuning Approach for Language Models (Shah et al., sustainlp 2023)

ACL

• Aditya Shah, Surendrabikram Thapa, Aneesh Jain, and Lifu Huang. 2023. ADEPT: Adapter-based Efficient Prompt Tuning Approach for Language Models. In Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), pages 121–128, Toronto, Canada (Hybrid). Association for Computational Linguistics.