Zobrazeno 1 - 3
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pro vyhledávání: '"Erofeeva, Aliia"'
We propose a method to transfer knowledge across neural machine translation (NMT) models by means of a shared dynamic vocabulary. Our approach allows to extend an initial model for a given language pair to cover new languages by adapting its vocabula
Externí odkaz:
http://arxiv.org/abs/1811.01137
Both research and commercial machine translation have so far neglected the importance of properly handling the spelling, lexical and grammar divergences occurring among language varieties. Notable cases are standard national varieties such as Brazili
Externí odkaz:
http://arxiv.org/abs/1811.01064
Autor:
Vu, Hoa Trong, Greco, Claudio, Erofeeva, Aliia, Jafaritazehjan, Somayeh, Linders, Guido, Tanti, Marc, Testoni, Alberto, Bernardi, Raffaella, Gatt, Albert
Capturing semantic relations between sentences, such as entailment, is a long-standing challenge for computational semantics. Logic-based models analyse entailment in terms of possible worlds (interpretations, or situations) where a premise P entails
Externí odkaz:
http://arxiv.org/abs/1806.05645