Results 31 to 40 of about 3,637,202 (294)
Building machine reading comprehension model from scratch [PDF]
, 2023 In this paper, we introduce a machine reading comprehension model and how we built this model from scratch. Reading comprehension is a crucial requisite for artificial intelligence applications, such as Question-Answering systems, chatbots, virtual ...
Yang, Zijian Győző +3 more
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A Survey on Explainability in Machine Reading Comprehension
CoRR, 2020 This paper presents a systematic review of benchmarks and approaches for explainability in Machine Reading Comprehension (MRC). We present how the representation and inference challenges evolved and the steps which were taken to tackle these challenges. We also present the evaluation methodologies to assess the performance of explainable systems.
Mokanarangan Thayaparan +2 more
openaire +2 more sources
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
doaj +1 more source
Answer Extraction Method for Reading Comprehension Based on Frame Semantics and GraphStructure [PDF]
Jisuanji kexue, 2023 Machine reading comprehension is one of the most challenging tasks in the field of natural language processing.With the continuous development of deep learning technology and the release of large-scale MRC datasets,the performance of MRC models keep ...
YANG Zhizhuo, XU Lingling, Zhang Hu, LI Ru
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Benchmarking Machine Reading Comprehension: A Psychological Perspective [PDF]
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021 Machine reading comprehension (MRC) has received considerable attention as a benchmark for natural language understanding. However, the conventional task design of MRC lacks explainability beyond the model interpretation, i.e., reading comprehension by a model cannot be explained in human terms.
Saku Sugawara +2 more
openaire +3 more sources
Benchmarking Robustness of Machine Reading Comprehension Models [PDF]
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021 Machine Reading Comprehension (MRC) is an important testbed for evaluating models' natural language understanding (NLU) ability. There has been rapid progress in this area, with new models achieving impressive performance on various benchmarks. However, existing benchmarks only evaluate models on in-domain test sets without considering their robustness
Chenglei Si +5 more
openaire +3 more sources
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
core +1 more source
Benchmarking Machine Translation Efficacy for Teaching EAP Reading Comprehension Skills [PDF]
Fanāvarī-i āmūzish, 2023 Background and Objectives: Although Machine Translation (MT) is extensively researched within the field of Artificial Intelligence (AI) and translation studies, few studies have attempted to implement MT output in foreign language teaching (FLT).
V. Mirzaeian, M. Maghsoudi
doaj +1 more source
A Survey on Neural Machine Reading Comprehension
CoRR, 2019 Enabling a machine to read and comprehend the natural language documents so that it can answer some questions remains an elusive challenge. In recent years, the popularity of deep learning and the establishment of large-scale datasets have both promoted the prosperity of Machine Reading Comprehension.
Boyu Qiu +3 more
openaire +3 more sources
Artificial intelligence (machine learning) in the psychology of learning: Unveiling new insights and directions [PDF]
مجله علوم روانشناختی, 2023 Background: The intersection of artificial intelligence (AI), psychology and applied linguistics particularly in the realm of language learning, has opened up a fascinating avenue for exploring the intricate processes and mechanisms underlying human ...
Nora Darjazini +3 more
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