@inproceedings{chu-etal-2022-hit,
title = "{HIT} at {S}em{E}val-2022 Task 2: Pre-trained Language Model for Idioms Detection",
author = "Chu, Zheng and
Yang, Ziqing and
Cui, Yiming and
Chen, Zhigang and
Liu, Ming",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.28",
doi = "10.18653/v1/2022.semeval-1.28",
pages = "221--227",
abstract = "The same multi-word expressions may have different meanings in different sentences. They can be mainly divided into two categories, which are literal meaning and idiomatic meaning. Non-contextual-based methods perform poorly on this problem, and we need contextual embedding to understand the idiomatic meaning of multi-word expressions correctly. We use a pre-trained language model, which can provide a context-aware sentence embedding, to detect whether multi-word expression in the sentence is idiomatic usage.",
}
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%0 Conference Proceedings
%T HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection
%A Chu, Zheng
%A Yang, Ziqing
%A Cui, Yiming
%A Chen, Zhigang
%A Liu, Ming
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F chu-etal-2022-hit
%X The same multi-word expressions may have different meanings in different sentences. They can be mainly divided into two categories, which are literal meaning and idiomatic meaning. Non-contextual-based methods perform poorly on this problem, and we need contextual embedding to understand the idiomatic meaning of multi-word expressions correctly. We use a pre-trained language model, which can provide a context-aware sentence embedding, to detect whether multi-word expression in the sentence is idiomatic usage.
%R 10.18653/v1/2022.semeval-1.28
%U https://aclanthology.org/2022.semeval-1.28
%U https://doi.org/10.18653/v1/2022.semeval-1.28
%P 221-227
Markdown (Informal)
[HIT at SemEval-2022 Task 2: Pre-trained Language Model for Idioms Detection](https://aclanthology.org/2022.semeval-1.28) (Chu et al., SemEval 2022)
ACL