Browsing by Author "Fernández, Raquel"

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  • Aina, Laura; Bernardi, Raffaella; Fernández, Raquel (CEUR Workshop Proceedings, 2018)
    In this paper, we investigate the relation between negated adjectives and antonyms in English using Distributional Semantics methods. Results show that, on the basis of contexts of use, a negated adjective (e.g., not cold) ...
  • 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 ...
  • Lazaridou, Angeliki; Chrupała, Grzegorz; Fernández, Raquel; Baroni, Marco (ACL (Association for Computational Linguistics), 2016)
    Children learn the meaning of words by being exposed to perceptually rich situations (linguistic discourse, visual scenes, etc). Current computational learning models typically simulate these rich situations through ...
  • Aina, Laura; Bernardi, Raffaella; Fernández, Raquel (Associazione Italiana di Linguistica Computazionale, 2019)
    We investigate the relation between negated adjectives and antonyms pairs in English (e.g., not cold vs. hot - cold) using Distributional Semantics. We build vector representations of a set of antonyms and their negations ...
  • 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 ...
  • Fernández, Raquel; Martin, Alberto, 1974- (2014-12-01)
    We present a simple model of sovereign debt crises in which a country chooses its optimal mix of short and long-term bonds subject to standard contracting frictions: the country cannot commit to repay its debts nor to a ...

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