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Mar, 2022
Clozer: 适应性数据增强用于填空式阅读理解
Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension
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Holy Lovenia, Bryan Wilie, Willy Chung, Min Zeng, Samuel Cahyawijaya...
TL;DR
本文提出了Clozer，一种基于序列标注的填空答案提取方法，用于TAPT从而提高模型性能，并在多项选择式MRC任务上进行了实验，证明Clozer在能够独立识别黄金答案的同时，提高了TAPT的有效性。
Abstract
task-adaptive pre-training
(TAPT) alleviates the lack of
labelled data
and provides performance lift by adapting unlabelled data to downstream task. Unfortunately, existing adaptations mainly involve deterministi
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