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Browsing Congressos (Departament de Traducció i Ciències del Llenguatge) by Author "Sorodoc, Ionut-Teodor"

Browsing Congressos (Departament de Traducció i Ciències del Llenguatge) by Author "Sorodoc, Ionut-Teodor"

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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; Aina, Laura; Boleda, Gemma (ACL (Association for Computational Linguistics), 2022)
    To successfully account for language, computational models need to take into account both the linguistic context (the content of the utterances) and the extra-linguistic context (for instance, the participants in a dialogue). ...
  • 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. ...
  • Sorodoc, Ionut-Teodor; Boleda, Gemma; Baroni, Marco (ACL (Association for Computational Linguistics), 2021)
    In recent years, the NLP community has shown increasing interest in analysing how deep learning models work. Given that large models trained on complex tasks are difficult to inspect, some of this work has focused ...
  • 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 ...
  • Sorodoc, Ionut-Teodor; Gulordava, Kristina; Boleda, Gemma (ACL (Association for Computational Linguistics), 2020)
    Language models keep track of complex information about the preceding context – including, e.g., syntactic relations in a sentence. We investigate whether they also capture information beneficial for resolving pronominal ...
  • 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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