ExpMRC: explainability evaluation for machine reading comprehension
Heliyon, 2022 Achieving human-level performance on some Machine Reading Comprehension (MRC) datasets is no longer challenging with the help of powerful Pre-trained Language Models (PLMs).
Yiming Cui +4 more
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Neural Machine Reading Comprehension: Methods and Trends
Applied Sciences, 2019 Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques over the past few years.
Shanshan Liu +4 more
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A Survey on Machine Reading Comprehension—Tasks, Evaluation Metrics and Benchmark Datasets
Applied Sciences, 2020 Machine Reading Comprehension (MRC) is a challenging Natural Language Processing (NLP) research field with wide real-world applications. The great progress of this field in recent years is mainly due to the emergence of large-scale datasets and deep ...
Changchang Zeng +4 more
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FedQAS: Privacy-Aware Machine Reading Comprehension with Federated Learning
Applied Sciences, 2022 Machine reading comprehension (MRC) of text data is a challenging task in Natural Language Processing (NLP), with a lot of ongoing research fueled by the release of the Stanford Question Answering Dataset (SQuAD) and Conversational Question Answering ...
Addi Ait-Mlouk +3 more
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Attribute Value Extraction Method Based on Machine Reading Comprehension Model and Crowdsourcing Verification [PDF]
Jisuanji gongcheng, 2021 Due to the high noise characteristics of Internet corpus,traditional extraction methods based on attribute values suffer from increased labor costs and lack of training sets.This paper proposes an entity attribute value extraction method based on machine
FENG Suo, LIU Jingping, JIANG Haiyun, XIAO Yanghua
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Research Progress of Multi-Hop Machine Reading Comprehension [PDF]
Jisuanji gongcheng, 2021 Compared with common single-hop Machine Reading Comprehension(MRC), Multi-Hop MRC(MHMRC) needs multi-hop reasoning from given multiple documents or paragraphs to understand and answer complex questions.Though MHMRC is extremely challenging, it is closer ...
SU Ke, HUANG Ruiyang, ZHANG Jianpeng, YU Shiyuan, HU Nan
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Multiple Choice Machine Reading Comprehension Based on Temporal Convolutional Network [PDF]
Jisuanji gongcheng, 2020 As a challenging task in the field of natural language processing,machine reading comprehension aims to answer questions related to articles and requires complex semantic reasoning.To solve the problem of information loss and inability to capture the ...
YANG Shanshan, JIANG Lifen, SUN Huazhi, MA Chunmei
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Chinese Machine Reading Comprehension Based on Hybrid Attention Mechanism [PDF]
Jisuanji gongcheng, 2022 The pre-training language model performs well in the field of machine reading comprehension.Compared with English machine reading comprehension, the reading comprehension model based on the pre-training language model performs slightly worse in ...
LIU Gaojun, LI Yaxin, DUAN Jianyong
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Learn a prior question-aware feature for machine reading comprehension
Frontiers in Physics, 2022 Machine reading comprehension aims to train machines to comprehend a given context and then answer a series of questions according to their understanding of the context. It is the cornerstone of conversational reading comprehension and question answering
Yu Zhang, Bo Shen, Xing Cao
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Multi-Document Neural Reading Comprehension Based on Bi-Directional Attention Mechanism [PDF]
Jisuanji gongcheng, 2020 Machine Reading Comprehension(MRC) is a question and answer task that automatically generates or extracts corresponding answers for a given text and specific questions.This task is of great significance to evaluating the understanding of computer systems
TANG Hongxuan, WU Kaili, ZHU Mengmeng, HONG Yu
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