Results 61 to 70 of about 3,637,202 (294)
Machine Reading Comprehension Model Based on MacBERT and Adversarial Training [PDF]
Jisuanji gongchengMachine reading comprehension is designed to allow machines to understand natural language texts, resembling humans, and perform question-answering tasks accordingly.
ZHOU Zhaochen, FANG Qingmao, WU Xiaohong, HU Ping, HE Xiaohai
doaj +1 more source
ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension
CoRR, 2019 Reading comprehension is one of the crucial tasks for furthering research in natural language understanding. A lot of diverse reading comprehension datasets have recently been introduced to study various phenomena in natural language, ranging from simple paraphrase matching and entity typing to entity tracking and understanding the implications of the ...
Dheeru Dua +4 more
openaire +3 more sources
SQL Generation via Machine Reading Comprehension [PDF]
Proceedings of the 28th International Conference on Computational Linguistics, 2020 Text-to-SQL systems offers natural language interfaces to databases, which can automatically generates SQL queries given natural language questions. On the WikiSQL benchmark, state-of- the-art text-to-SQL systems typically take a slot-filling approach by building several specialized models for each type of slot.
Zeyu Yan +3 more
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Towards Knowledge Enhanced Language Model for Machine Reading Comprehension
IEEE Access, 2020 Machine reading comprehension is a crucial and challenging task in natural language processing (NLP). Recently, knowledge graph (KG) embedding has gained massive attention as it can effectively provide side information for downstream tasks. However, most
Peizhu Gong +3 more
doaj +1 more source
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source
Cooperative Self-training of Machine Reading Comprehension
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022 Pretrained language models have significantly improved the performance of downstream language understanding tasks, including extractive question answering, by providing high-quality contextualized word embeddings. However, training question answering models still requires large amounts of annotated data for specific domains.
Hongyin Luo +4 more
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A Vietnamese Dataset for Evaluating Machine Reading Comprehension [PDF]
Proceedings of the 28th International Conference on Computational Linguistics, 2020 Over 97 million people speak Vietnamese as their native language in the world. However, there are few research studies on machine reading comprehension (MRC) for Vietnamese, the task of understanding a text and answering questions related to it. Due to the lack of benchmark datasets for Vietnamese, we present the Vietnamese Question Answering Dataset ...
Kiet Van Nguyen +3 more
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Intelligent Systems with Applications, 2023 Deep neural networks, despite their remarkable success in various language understanding tasks, have been found vulnerable to adversarial attacks and subtle input perturbations, revealing a robustness shortfall.
Jingliang Fang +5 more
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Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Read + Verify: Machine Reading Comprehension with Unanswerable Questions
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 Machine reading comprehension with unanswerable questions aims to abstain from answering when no answer can be inferred. In addition to extract answers, previous works usually predict an additional “no-answer” probability to detect unanswerable cases.
Minghao Hu +5 more
openaire +4 more sources