用自回归语言模型和反向翻译逼近SMM4H

Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task Pub Date : 2021-06-01 DOI:10.18653/V1/2021.SMM4H-1.32

Joseph Cornelius, Tilia Ellendorff, Fabio Rinaldi

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引用次数: 1

摘要

我们描述了我们提交给第6版的健康应用社交媒体挖掘(SMM4H)共享任务。我们的团队(OGNLP)参与了子任务:推文自我报告COVID-19潜在病例的分类(任务5)。对于我们的提交，我们使用基于自回归转换模型(XLNet)和反向翻译的系统来平衡数据集。

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Approaching SMM4H with auto-regressive language models and back-translation

We describe our submissions to the 6th edition of the Social Media Mining for Health Applications (SMM4H) shared task. Our team (OGNLP) participated in the sub-task: Classification of tweets self-reporting potential cases of COVID-19 (Task 5). For our submissions, we employed systems based on auto-regressive transformer models (XLNet) and back-translation for balancing the dataset.

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Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task

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