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pro vyhledávání: '"Tokarchuk, Evgeniia"'
Autor:
Tokarchuk, Evgeniia, Niculae, Vlad
Continuous-output neural machine translation (CoNMT) replaces the discrete next-word prediction problem with an embedding prediction. The semantic structure of the target embedding space (i.e., closeness of related words) is intuitively believed to b
Externí odkaz:
http://arxiv.org/abs/2310.20620
Data processing is an important step in various natural language processing tasks. As the commonly used datasets in named entity recognition contain only a limited number of samples, it is important to obtain additional labeled data in an efficient a
Externí odkaz:
http://arxiv.org/abs/2110.05892
Autor:
Tokarchuk, Evgeniia, Rosendahl, Jan, Wang, Weiyue, Petrushkov, Pavel, Lancewicki, Tomer, Khadivi, Shahram, Ney, Hermann
Pivot-based neural machine translation (NMT) is commonly used in low-resource setups, especially for translation between non-English language pairs. It benefits from using high resource source-pivot and pivot-target language pairs and an individual s
Externí odkaz:
http://arxiv.org/abs/2109.13097
Autor:
Tokarchuk, Evgeniia, Rosendahl, Jan, Wang, Weiyue, Petrushkov, Pavel, Lancewicki, Tomer, Khadivi, Shahram, Ney, Hermann
Complex natural language applications such as speech translation or pivot translation traditionally rely on cascaded models. However, cascaded models are known to be prone to error propagation and model discrepancy problems. Furthermore, there is no
Externí odkaz:
http://arxiv.org/abs/2109.12950