ExpMRC: explainability evaluation for machine reading comprehension [PDF]
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 [PDF]
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
doaj +6 more sources
Multilingual multi-aspect explainability analyses on machine reading comprehension models [PDF]
iScience, 2022 Summary: Achieving human-level performance on some of the machine reading comprehension (MRC) datasets is no longer challenging with the help of powerful pre-trained language models (PLMs).
Yiming Cui +5 more
doaj +2 more sources
Integrate Candidate Answer Extraction with Re-Ranking for Chinese Machine Reading Comprehension [PDF]
Entropy, 2021 Machine Reading Comprehension (MRC) research concerns how to endow machines with the ability to understand given passages and answer questions, which is a challenging problem in the field of natural language processing.
Junjie Zeng +3 more
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S2‐Net: Machine reading comprehension with SRU‐based self‐matching networks
ETRI Journal, 2019 Machine reading comprehension is the task of understanding a given context and finding the correct response in that context. A simple recurrent unit (SRU) is a model that solves the vanishing gradient problem in a recurrent neural network (RNN) using a ...
Cheoneum Park +8 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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