Zobrazeno 1 - 5
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pro vyhledávání: '"Verna Dankers"'
Autor:
Anna Langedijk, Verna Dankers, Phillip Lippe, Sander Bos, Bryan Cardenas Guevara, Helen Yannakoudakis, Ekaterina Shutova
Meta-learning, or learning to learn, is a technique that can help to overcome resource scarcity in cross-lingual NLP problems, by enabling fast adaptation to new tasks. We apply model-agnostic meta-learning (MAML) to the task of cross-lingual depende
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6185a079390dfaae0b607c5625306563
http://arxiv.org/abs/2104.04736
http://arxiv.org/abs/2104.04736
Publikováno v:
Proceedings of the 25th Conference on Computational Natural Language Learning.
Publikováno v:
IJCAI
Despite a multitude of empirical studies, little consensus exists on whether neural networks are able to generalise compositionally. As a response to this controversy, we present a set of tests that provide a bridge between, on the one hand, the vast
Publikováno v:
Fig-Lang@ACL
Existing approaches to metaphor processing typically rely on local features, such as immediate lexico-syntactic contexts or information within a given sentence. However, a large body of corpus-linguistic research suggests that situational information
Publikováno v:
Journal of Artificial Intelligence Research
Despite a multitude of empirical studies, little consensus exists on whether neural networks are able to generalise compositionally, a controversy that, in part, stems from a lack of agreement about what it means for a neural model to be compositiona
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::648106e9b01e3f9bab6652669fa6b704
http://arxiv.org/abs/1908.08351
http://arxiv.org/abs/1908.08351