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pro vyhledávání: '"Merello, Simone"'
Autor:
Plekhanov, Mikhail, Kassner, Nora, Popat, Kashyap, Martin, Louis, Merello, Simone, Kozlovskii, Borislav, Dreyer, Frédéric A., Cancedda, Nicola
Entity Linking is one of the most common Natural Language Processing tasks in practical applications, but so far efficient end-to-end solutions with multilingual coverage have been lacking, leading to complex model stacks. To fill this gap, we releas
Externí odkaz:
http://arxiv.org/abs/2306.08896
Autor:
Atzeni, Mattia, Plekhanov, Mikhail, Dreyer, Frédéric A., Kassner, Nora, Merello, Simone, Martin, Louis, Cancedda, Nicola
Entity linking methods based on dense retrieval are an efficient and widely used solution in large-scale applications, but they fall short of the performance of generative models, as they are sensitive to the structure of the embedding space. In orde
Externí odkaz:
http://arxiv.org/abs/2305.12027
Publikováno v:
In Expert Systems With Applications 30 November 2019 135:60-70
