@inproceedings{liu-etal-2023-small,
title = "Small is the New Big: Pre-finetuned compact models are better for Asynchronous Active Learning",
author = "Liu, Dantong and
Pavani, Kaushik and
Dasgupta, Sunny",
editor = "Sadat Moosavi, Nafise and
Gurevych, Iryna and
Hou, Yufang and
Kim, Gyuwan and
Kim, Young Jin and
Schuster, Tal and
Agrawal, Ameeta",
booktitle = "Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)",
month = jul,
year = "2023",
address = "Toronto, Canada (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.sustainlp-1.7/",
doi = "10.18653/v1/2023.sustainlp-1.7",
pages = "110--120"
}
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%0 Conference Proceedings
%T Small is the New Big: Pre-finetuned compact models are better for Asynchronous Active Learning
%A Liu, Dantong
%A Pavani, Kaushik
%A Dasgupta, Sunny
%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 liu-etal-2023-small
%R 10.18653/v1/2023.sustainlp-1.7
%U https://aclanthology.org/2023.sustainlp-1.7/
%U https://doi.org/10.18653/v1/2023.sustainlp-1.7
%P 110-120
Markdown (Informal)
[Small is the New Big: Pre-finetuned compact models are better for Asynchronous Active Learning](https://aclanthology.org/2023.sustainlp-1.7/) (Liu et al., sustainlp 2023)
ACL