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Domain Adaptive Pretraining for Multilingual Acronym Extraction

2022-06-30 12:11:39
Usama Yaseen, Stefan Langer
arXiv_CL
         
Abstract

This paper presents our findings from participating in the multilingual acronym extraction shared task SDU@AAAI-22. The task consists of acronym extraction from documents in 6 languages within scientific and legal domains. To address multilingual acronym extraction we employed BiLSTM-CRF with multilingual XLM-RoBERTa embeddings. We pretrained the XLM-RoBERTa model on the shared task corpus to further adapt XLM-RoBERTa embeddings to the shared task domain(s). Our system (team: SMR-NLP) achieved competitive performance for acronym extraction across all the languages.

Abstract (translated)

URL

https://arxiv.org/abs/2206.15221

PDF

https://arxiv.org/pdf/2206.15221.pdf

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