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1
Evaluation of Deep Learning-Based Automated Detection of Primary Spine Tumors on MRI Using the Turing Test
In: Front Oncol (2022)
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2
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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3
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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4
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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5
Exploiting Scene Graphs for Human-Object Interaction Detection ...
He, Tao; Gao, Lianli; Song, Jingkuan. - : arXiv, 2021
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6
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages ...
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7
CrossSum: Beyond English-Centric Cross-Lingual Abstractive Text Summarization for 1500+ Language Pairs ...
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8
Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection ...
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9
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages ...
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10
XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages
In: The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Online, 2 August 2021 (2021)
Abstract: Contemporary works on abstractive text summarization have focused primarily on highresource languages like English, mostly due to the limited availability of datasets for low/midresource ones. In this work, we present XLSum, a comprehensive and diverse dataset comprising 1 million professionally annotated article-summary pairs from BBC, extracted using a set of carefully designed heuristics. The dataset covers 44 languages ranging from low to high-resource, for many of which no public dataset is currently available. XL-Sum is highly abstractive, concise, and of high quality, as indicated by human and intrinsic evaluation. We fine-tune mT5, a state-of-theart pretrained multilingual model, with XLSum and experiment on multilingual and lowresource summarization tasks. XL-Sum induces competitive results compared to the ones obtained using similar monolingual datasets: we show higher than 11 ROUGE-2 scores on 10 languages we benchmark on, with some of them exceeding 15, as obtained by multilingual training. Additionally, training on low-resource languages individually also provides competitive performance. To the best of our knowledge, XL-Sum is the largest abstractive summarization dataset in terms of the number of samples collected from a single source and the number of languages covered. We are releasing our dataset and models to encourage future research on multilingual abstractive summarization. The resources can be found at https://github. com/csebuetnlp/xl-sum.
URL: https://doi.org/10.18653/v1/2021.findings-acl.413
http://hdl.handle.net/1959.3/462187
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11
Oral microbiota transplantation fights against head and neck radiotherapy-induced oral mucositis in mice
In: Comput Struct Biotechnol J (2021)
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12
Universal Dependencies 2.7
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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13
Universal Dependencies 2.6
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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14
Knowledge-enriched, Type-constrained and Grammar-guided Question Generation over Knowledge Bases ...
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15
The influence of initial defect morphology of alveolar ridge on volumetric change of grafted bone following guided bone regeneration in the anterior maxilla region: an exploratory retrospective study
In: Ann Transl Med (2020)
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16
Themenschwerpunkt Deutsch als Fremdsprache in China
Li, Yuan [Herausgeber]. - Berlin : De Gruyter, 2019
DNB Subject Category Language
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17
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
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18
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
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19
Massively Multilingual Transfer for NER ...
Rahimi, Afshin; Li, Yuan; Cohn, Trevor. - : arXiv, 2019
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20
Massively multilingual transfer for NER
Rahimi, Afshin; Li, Yuan; Cohn, Trevor. - : Association for Computational Linguistics -ACL, 2019
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