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Continual Domain Adaptation for Machine Reading Comprehension
[article]
2020
pre-print
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Machine reading comprehension (MRC) has become a core component in a variety of natural language processing (NLP) applications such as question answering and dialogue systems. ...
To tackle such a challenge, in this work, we introduce the Continual Domain Adaptation (CDA) task for MRC. So far as we know, this is the first study on the continual learning perspective of MRC. ...
., machine reading comprehension and continual learning. Then, we introduce various datasets for machine reading comprehension research in detail. ...
doi:10.1145/3340531.3412047
arXiv:2008.10874v1
fatcat:e7gbo4qndjejrlltyx23ddblqi
Continual Machine Reading Comprehension via Uncertainty-aware Fixed Memory and Adversarial Domain Adaptation
2022
Findings of the Association for Computational Linguistics: NAACL 2022
unpublished
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Continual Machine Reading Comprehension aims to incrementally learn from a continuous data stream across time without access the previous seen data, which is crucial for the development of real-world MRC ...
In this paper, MA-MRC, a continual MRC model with uncertainty-aware fixed Memory and Adversarial domain adaptation, is proposed. ...
., China Joint Research Center for Industrial Intelligence and Internet of Things. ...
doi:10.18653/v1/2022.findings-naacl.179
fatcat:2fsfjkbwpjhg7j77ybart3idgm
Task Transfer and Domain Adaptation for Zero-Shot Question Answering
[article]
2022
arXiv
pre-print
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Our approach outperforms Domain-Adaptive Pretraining on downstream domain-specific reading comprehension tasks in 3 out of 4 domains. ...
We evaluate zero-shot performance on domain-specific reading comprehension tasks by combining task transfer with domain adaptation to fine-tune a pretrained model with no labelled data from the target ...
Acknowledgement We thank Sam Bowman for providing key feedback throughout our research. ...
arXiv:2206.06705v1
fatcat:wkwwzsnbxngj5g6nfjr7pfkwka
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension Task
[article]
2022
arXiv
pre-print
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We present an adversarial learning-based domain adaptation framework for the biomedical machine reading comprehension task (BioADAPT-MRC), a neural network-based method to address the discrepancies in ...
Biomedical machine reading comprehension (biomedical-MRC) aims to comprehend complex biomedical narratives and assist healthcare professionals in retrieving information from them. ...
Figure 1 : 1 Figure 1: BioADAPT-MRC: an adversarial learning-based domain adaptation framework for biomedical machine reading comprehension task. ...
arXiv:2202.13174v2
fatcat:3ikhmt2dg5hohbu2wbshl3amw4
Machine Reading Comprehension-Enabled Public Service Information System: A Large-Scale Dataset and Neural Network Models
2022
Wireless Communications and Mobile Computing
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Machine reading comprehension is a new research hotspot in the field of machine learning, which has great application potential in PSIS systems. ...
In this paper, we explore the application of machine reading comprehension to the field of Chinese public service information systems from scratch. ...
of machine reading comprehension (MRC) technology in PSIS systems will provide many advantages for public services. ...
doi:10.1155/2022/7088126
fatcat:bfrswwv4trhijphozqhavvxeoi
Page 1358 of Linguistics and Language Behavior Abstracts: LLBA Vol. 28, Issue 3
[page]
1994
Linguistics and Language Behavior Abstracts: LLBA
Preserved Fulltext
The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
/strategies differences, linear vs hypertext for- mat; experiments; 9404731
reading experiments, moving window generator use; effective visual field size measurement; college students; 9404755
reading/ ...
; empirical data; English-speaking Spanish as a for- eign language learners; 9406084
Italian basic vocabulary database structure/fields content; 9406100
machine translation systems, evaluation metrics ...
Machine Reading at Scale: A Search Engine for Scientific and Academic Research
2022
Systems
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It combines state-of-the-art algorithms for information retrieval and reading comprehension tasks to extract meaningful answers from a corpus of scientific documents. ...
In this work, a new search engine is proposed, addressing machine reading at scale in the context of scientific and academic research. ...
In [38] , Cai et al. analyzed the claim that fine-tuning a model for reading comprehension, such as BERT, improves its results on more specific domains. ...
doi:10.3390/systems10020043
fatcat:z6pmelshpbfuvdsxe3m6xrejli
Book review on cognitive engineering and safety organization in air traffic management
2018
Cognition, Technology & Work
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This is a very interesting book to read. It demonstrates why Cognitive Science is necessary for dealing with complex environments involving humans and machines. ...
Therefore, this book is perfect for marrying the human-machine-interaction (HMI) issues of modern technology and domainspecific requirements. ...
In essence, this book is certainly valuable for achieving a comprehensive view of the Cognitive Science aspects relevant for ATM and of the methods most commonly applied for problem-solving and assessment ...
doi:10.1007/s10111-018-0532-9
fatcat:p2d6sqc7prgvbncqcu5rzy2thm
End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training
[article]
2020
arXiv
pre-print
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End-to-end question answering (QA) requires both information retrieval (IR) over a large document collection and machine reading comprehension (MRC) on the retrieved passages. ...
Furthermore, given little or no labeled data, effective adaptation of QA systems can also be challenging in such target domains. ...
Hence they must include both an information retrieval (IR) and a machine reading comprehension (MRC) component. ...
arXiv:2012.01414v1
fatcat:rq7l4dvycrbnvpvdujxokeqgoa
Forget Me Not: Reducing Catastrophic Forgetting for Domain Adaptation in Reading Comprehension
[article]
2020
arXiv
pre-print
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2019 pre-print arXiv:1911.00202v1 fatcat:voflem6ef5hflgflk73a3jpghaOther Versions
The creation of large-scale open domain reading comprehension data sets in recent years has enabled the development of end-to-end neural comprehension models with promising results. ...
We introduce new auxiliary penalty terms and observe the best performance when a combination of auxiliary penalty terms is used to regularise the fine-tuning process for adapting comprehension models. ...
(Wiese, Weissenborn, and Neves 2017) explore supervised domain adaptation for reading comprehension, by pretraining their model first on large open-domain comprehension data and fine-tuning it further ...
arXiv:1911.00202v3
fatcat:rkhc5v2bkzflhdoww2u7mts3pq
From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap
[article]
2020
arXiv
pre-print
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More importantly, by leveraging machine reading comprehension datasets, our method outperforms the existing approaches by many a large margin in few-shot scenarios when the availability of in-domain data ...
In this paper, we propose using machine reading comprehension (RC) in state tracking from two perspectives: model architectures and datasets. ...
Accordingly, we propose two machine reading comprehension models for dialogue state tracking. ...
arXiv:2004.05827v1
fatcat:ybzyjysxenh4dp55yurmarviuu
Advances in Multi-turn Dialogue Comprehension: A Survey
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2110.04984v1 fatcat:ecifyqdnbbc5ve6texzgoqteu4
Among these studies, the fundamental yet challenging type of task is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding. ...
In this paper, we review the previous methods from the technical perspective of dialogue modeling for the dialogue comprehension task. ...
machine reading comprehension , in which way we bridge the gap between the dialogue modeling and com-prehension, and hopefully benefit the future researches with the cutting-edge PrLMs. ...
arXiv:2110.04984v2
fatcat:4i4svd2oyvdhhasqx2ungtppue
Advances in Multi-turn Dialogue Comprehension: A Survey
[article]
2021
arXiv
pre-print
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Among these studies, the fundamental yet challenging type of task is dialogue comprehension whose role is to teach the machines to read and comprehend the dialogue context before responding. ...
In this paper, we review the previous methods from the technical perspective of dialogue modeling for the dialogue comprehension task. ...
machine reading comprehension , in which way we bridge the gap between the dialogue modeling and com-prehension, and hopefully benefit the future researches with the cutting-edge PrLMs. ...
arXiv:2103.03125v2
fatcat:62p6ase66jbhnhm77xlp5ulvre
Computer games for the teaching of reading
1982
Behavior Research Methods
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Second, I discuss several issues of man-machine interaction that are particularly appropriate in building programs for people who do not read well. ...
After that, I briefly address the issue of adapting to individual style differences. ...
For example, perhaps the machine could pronounce any word the child touched. allowing the child to continue understanding text even if he is tripped up by a word or two. ...
doi:10.3758/bf03202157
fatcat:n5g62vrxozcndaqkos3553ie3u
Real-Time Scoring of an Oral Reading Assessment on Mobile Devices
2018
Interspeech 2018
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By combining features derived from word embedding with the normalized number of common types, we achieved a human-machine correlation coefficient of 0.90 at the participant level for comprehension scores ...
We discuss the real-time scoring logic for a self-administered oral reading assessment on mobile devices (Moby.Read) to measure the three components of children's oral reading fluency skills: words correct ...
Scoring of expression and comprehension will emphasize reading for meaning instead of reading for speed. Automatic scoring can reduce the need for teacher training and help ensure consistency. ...
doi:10.21437/interspeech.2018-34
dblp:conf/interspeech/Cheng18
fatcat:svdvngaoovc7rkhoievajhm5qy
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