Multi-Granularity Matching Network for Multi-Paragraph Machine Reading Comprehension
نویسندگان
چکیده
منابع مشابه
Simple and Effective Multi-Paragraph Reading Comprehension
We consider the problem of adapting neural paragraph-level question answering models to the case where entire documents are given as input. Our proposed solution trains models to produce well calibrated confidence scores for their results on individual paragraphs. We sample multiple paragraphs from the documents during training, and use a sharednormalization training objective that encourages t...
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We present a dual contribution to the task of machine reading-comprehension: a technique for creating large-sized machine-comprehension (MC) datasets using paragraph-vector models; and a novel, hybrid neural-network architecture that combines the representation power of recurrent neural networks with the discriminative power of fully-connected multi-layered networks. We use the MC-dataset gener...
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This project explores the multi-perspective context matching method for the task of reading comprehension using the SQuAD data set. The original six layer model presents an interesting system for exploring deep learning architectures and their implementations on Tensorflow.The first step was to design an efficient implementation of this complex model on Tensorflow. The second step, and the aim ...
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2021
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/1871/1/012091