TT-Net: Topic Transfer-Based Neural Network for Conversational Reading Comprehension
IEEE Access, 2019 Conversational machine reading comprehension (MRC) is a new question answering task, which is more challenging compared to traditional single-turn MRC since it requires a better understanding of conversation history. In this paper, a novel neural network
Gu Yingjie, Gui Xiaolin, Li Defu
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A Densely Connected Encoder Stack Approach for Multi-type Legal Machine Reading Comprehension
, 2020 Legal machine reading comprehension (MRC) is becoming increasingly important as the number of legal documents rapidly grows. Currently, the main approach of MRC is the deep neural network based model which learns multi-level semantic information with ...
Li, Lin +5 more
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Retrospective Reader for Machine Reading Comprehension
, 2021 Machine reading comprehension (MRC) is an AI challenge that requires machines to determine the correct answers to questions based on a given passage. MRC systems must not only answer questions when necessary but also tactfully abstain from answering when
Zhang, Zhuosheng +2 more
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Multigranularity Syntax Guidance with Graph Structure for Machine Reading Comprehension
Applied Sciences, 2022 In recent years, pre-trained language models, represented by the bidirectional encoder representations from transformers (BERT) model, have achieved remarkable success in machine reading comprehension (MRC).
Chuanyun Xu +4 more
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Reading comprehension in developmental disorders of language and communication [PDF]
, 2011 Background: Deficits in reading airment (SLI), Down syndrome (DS) and autism spectrum disorders (ASD). Methods: In this review (based on a search of the ISI Web of Knowledge database to 2011), the Simple View of Reading is used as a framework for ...
Ricketts, Jessie, Jessie Ricketts
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Electronic Medical Record Entity Recognition via Machine Reading Comprehension and Biaffine
Discrete Dynamics in Nature and Society, 2021 The entity recognition of Chinese electronic medical record is of great significance to medical decision-making. The main process of entity recognition is sequence tagging, which has problems such as nested entity and boundary prediction.
Jun Cao +6 more
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Judicial nested named entity recognition method with MRC framework
International Journal of Cognitive Computing in Engineering, 2023 Judicial named entity recognition (JNER) is a basic task of judicial intelligence and judicial service informatization. At present, the research of JNER has attracted extensive attention.
Hu Zhang +4 more
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To get hold of the wrong end of the stick : reasons for poor idiom understanding in children with reading comprehension difficulties. [PDF]
, 2008 Purpose: The aim was to identify the source of idiom understanding difficulties in children with specific reading comprehension failure. Method: Two groups (Ns=15) of 9- to 10-year-olds participated. One group had age-appropriate word reading and reading
Cain, Kate, Towse, Andrea S.
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Applied Sciences, 2022 Answering different multi-choice machine reading comprehension (MRC) questions generally requires different information due to the abundant diversity of the questions, options and passages.
Ziwei Bai +4 more
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Improved Machine Reading Comprehension Using Data Validation for Weakly Labeled Data
IEEE Access, 2020 Machine reading comprehension (MRC) is a natural language processing task wherein a given question is answered according to a holistic understanding of a given context.
Yunyeong Yang, Sangwoo Kang, Jungyun Seo
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