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- W4287670902 abstract "We describe our system for WNUT-2020 shared task on the identification of informative COVID-19 English tweets. Our system is an ensemble of various machine learning methods, leveraging both traditional feature-based classifiers as well as recent advances in pre-trained language models that help in capturing the syntactic, semantic, and contextual features from the tweets. We further employ pseudo-labelling to incorporate the unlabelled Twitter data released on the pandemic. Our best performing model achieves an F1-score of 0.9179 on the provided validation set and 0.8805 on the blind test-set." @default.
- W4287670902 created "2022-07-25" @default.
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- W4287670902 date "2020-09-08" @default.
- W4287670902 modified "2023-09-23" @default.
- W4287670902 title "LynyrdSkynyrd at WNUT-2020 Task 2: Semi-Supervised Learning for Identification of Informative COVID-19 English Tweets" @default.
- W4287670902 doi "https://doi.org/10.48550/arxiv.2009.03849" @default.
- W4287670902 hasPublicationYear "2020" @default.
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