Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Huiyuan Lai"'
Publikováno v:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Style transfer aims to rewrite a source text in a different target style while preserving its content. We propose a novel approach to this task that leverages generic resources, and without using any task-specific parallel (source-target) data outper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::255bb07d0f0107bf6f4801bc3c419a8c
http://arxiv.org/abs/2109.04543
http://arxiv.org/abs/2109.04543
Publikováno v:
Optik. 181:898-905
We propose a method to preliminarily determine the thicknesses of bulk MoS2 layers based on their colours. The reflectance spectra of thin-layer and bulk MoS2 on three substrates were calculated by using the finite-difference time-domain technique; t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8da82ae05cadcb55d4f48e639c25486
https://doi.org/10.1016/j.ijleo.2018.12.187
https://doi.org/10.1016/j.ijleo.2018.12.187
Publikováno v:
Multimedia Tools and Applications. 79:14609-14624
Semantic sentence matching, also known as calculation of text similarity, is one of the most important problems in natural language processing. Existing deep models mostly focus on the neural networks with attention mechanism. In this paper, we prese
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd3bec1205983fb9194d3e8062e6c9da
https://doi.org/10.1007/s11042-018-7063-5
https://doi.org/10.1007/s11042-018-7063-5
Autor:
Lorenzo De Mattei, Michele Cafagna, Huiyuan Lai, Felice Dell'Orletta, Malvina Nissim, Albert Gatt
Publikováno v:
University of Groningen
Proceedings of the 1st Workshop on Evaluating NLG Evaluation (EvalNLGEval'20)
Proceedings of the 1st Workshop on Evaluating NLG Evaluation (EvalNLGEval'20)
An ongoing debate in the NLG community concerns the best way to evaluate systems, with human evaluation often being considered the most reliable method, compared to corpus-based metrics. However, tasks involving subtle textual differences, such as st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3e65bc0fb66780ce09da3f84f9aea01
http://arxiv.org/abs/2101.01634
http://arxiv.org/abs/2101.01634
Publikováno v:
Cognitive Internet of Things: Frameworks, Tools and Applications ISBN: 9783030049454
Semantic sentence matching is a fundamental technology in natural language processing. In the previous work, neural networks with attention mechanism have been successfully extended to semantic matching. However, existing deep models often simply use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6232dc852affe5aba195958c50dd2922
https://doi.org/10.1007/978-3-030-04946-1_22
https://doi.org/10.1007/978-3-030-04946-1_22
Publikováno v:
University of Groningen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::bf2d882d4002b305dc0f3bdcd6064b3a
https://research.rug.nl/en/publications/6ea45608-0e72-4b53-9482-2eff826127f0
https://research.rug.nl/en/publications/6ea45608-0e72-4b53-9482-2eff826127f0
Publikováno v:
University of Groningen
We exploit the pre-trained seq2seq model mBART for multilingual text style transfer. Using machine translated data as well as gold aligned English sentences yields state-of-the-art results in the three target languages we consider. Besides, in view o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2624168e22074d9dbcee699cc1cc257
https://research.rug.nl/en/publications/d6da73a8-7b48-4729-870f-9d21d9059a34
https://research.rug.nl/en/publications/d6da73a8-7b48-4729-870f-9d21d9059a34