D-net: A simple framework for improving the generalization of machine reading comprehension

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Abstract

In this paper, we introduce a simple system Baidu submitted for MRQA (Machine Reading for Question Answering) 2019 Shared Task that focused on generalization of machine reading comprehension (MRC) models. Our system is built on a framework of pretraining and fine-tuning, namely D-NET. The techniques of pre-trained language models and multi-task learning are explored to improve the generalization of MRC models and we conduct experiments to examine the effectiveness of these strategies. Our system is ranked at top 1 of all the participants in terms of averaged F1 score. Our codes and models will be released at PaddleNLP 1.

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APA

Li, H., Zhang, X., Liu, Y., Zhang, Y., Wang, Q., Zhou, X., … Wang, H. (2019). D-net: A simple framework for improving the generalization of machine reading comprehension. In MRQA@EMNLP 2019 - Proceedings of the 2nd Workshop on Machine Reading for Question Answering (pp. 212–219). Association for Computational Linguistics (ACL).

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