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Browsing Congressos (Departament de Traducció i Ciències del Llenguatge) by Subject "Computational semantics"

Browsing Congressos (Departament de Traducció i Ciències del Llenguatge) by Subject "Computational semantics"

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  • Boleda, Gemma; Aina, Laura; Silberer, Carina; Sorodoc, Ionut-Teodor; Westera, Matthijs (ACL (Association for Computational Linguistics), 2018)
    This paper describes our winning contribution to SemEval 2018 Task 4: Character Identification on Multiparty Dialogues. It is a simple, standard model with one key innovation, an entity library. Our results show that this ...
  • Sorodoc, Ionut-Teodor; Pezzelle, Sandro; Bernardi, Raffaella (ACL (Association for Computational Linguistics), 2018)
    The present work investigates whether different quantification mechanisms (set comparison, vague quantification, and proportional estimation) can be jointly learned from visual scenes by a multi-task computational model. ...
  • Boleda, Gemma; Gupta, Abhijeet; Padó, Sebastian (ACL (Association for Computational Linguistics), 2017)
    Word embeddings are supposed to provide easy access to semantic relations such as “male of” (man–woman). While this claim has been investigated for concepts, little is known about the distributional behavior of relations ...
  • Boleda, Gemma; Bernardi, Raffaella; Fernández, Raquel; Paperno, Denis (ACL (Association for Computational Linguistics), 2015)
    In this position paper we argue that an adequate semantic model must account for language in use, taking into account how discourse context affects the meaning of words and larger linguistic units. Distributional semantic ...
  • Boleda, Gemma; Gupta, Abhijeet; Baroni, Marco; Padó, Sebastian (ACL (Association for Computational Linguistics), 2015)
    Distributional methods have proven to excel at capturing fuzzy, graded aspects of meaning (Italy is more similar to Spain than to Germany). In contrast, it is difficult to extract the values of more specific attributes of ...
  • Boleda, Gemma; Padó, Sebastian; Pham, Nghia The; Baroni, Marco (ACL (Association for Computational Linguistics), 2017)
    Reference is the crucial property of language that allows us to connect linguistic expressions to the world. Modeling it requires handling both continuous and discrete aspects of meaning. Data-driven models excel at the ...
  • Boleda, Gemma; Sorodoc, Ionut-Teodor; Lazaridou, Angeliki; Herbelot, Aurélie; Pezzelle, Sandro; Bernardi, Raffaella (ACL (Association for Computational Linguistics), 2016)
    In this paper, we investigate whether a neural network model can learn the meaning of natural language quantifiers (no,some and all) from their use in visual contexts. We show that memory networks perform well in this ...
  • Boleda, Gemma; Del Tredici, Marco; Fernández, Raquel (ACL (Association for Computational Linguistics), 2019)
    We present the first exploration of meaning shift over short periods of time in online communities using distributional representations. We create a small annotated dataset and use it to assess the performance of a standard ...
  • Boleda, Gemma; Baroni, Marco; Padó, Sebastian (Springer, 2018)
    One of the most basic functions of language is to refer to objects in a shared scene. Modeling reference with continuous representations is challenging because it requires individuation, i.e., tracking and distinguishing ...
  • Boleda, Gemma; Aina, Laura; Silberer, Carina; Sorodoc, Ionut-Teodor; Westera, Matthijs (ACL (Association for Computational Linguistics), 2019)
    Humans use language to refer to entities in the external world. Motivated by this, in recent years several models that incorporate a bias towards learning entity representations have been proposed. Such entity-centric ...

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