Browsing by Author "Bernardi, Raffaella"

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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) ...
  • 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; 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; 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 ...
  • 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 ...
  • Bentivogli, Luisa; Bernardi, Raffaella; Marelli, Marco; Menini, Stefano; Baroni, Marco; Zamparelli, Roberto (Springer, 2016)
    This paper is an extended description of SemEval-2014 Task 1, the task on the evaluation of Compositional Distributional Semantics Models on full sentences. Systems participating in the task were presented with pairs of ...
  • Boleda, Gemma; Paperno, Denis; Kruszewski, German; Lazaridou, Angeliki; Pham, Quan Ngoc; Bernardi, Raffaella; Pezzelle, Sandro; Baroni, Marco; Fernandez, Raquel (ACL (Association for Computational Linguistics), 2016)
    We introduce LAMBADA, a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative passages sharing the characteristic that ...
  • Kruszewski, German; Paperno, Denis; Bernardi, Raffaella; Baroni, Marco (MIT Press, 2016)
    Logical negation is a challenge for distributional semantics, because predicates and their negations tend to occur in very similar contexts, and consequently their distributional vectors are very similar. Indeed, it is not ...

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