Browsing by Author "Boleda, Gemma"

Sort by: Order: Results:

  • Boleda, Gemma; Schulte im Walde, Sabine; Badia i Cardús, Antoni (ACL (Association for Computational Linguistics), 2012)
    We present a study on the automatic acquisition of semantic classes for Catalan adjectives from distributional and morphological information, with particular emphasis on polysemous adjectives. The aim is to distinguish ...
  • Silberer, Carina; Zarrieß, Sina; Boleda, Gemma (ACL (Association for Computational Linguistics), 2020)
    People choose particular names for objects, such as dog or puppy for a given dog. Object naming has been studied in Psycholinguistics, but has received relatively little attention in Computational Linguistics. We review ...
  • 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; Gulordava, Kristina; Aina, Laura (ACL (Association for Computational Linguistics), 2019)
    In neural network models of language, words are commonly represented using context invariant representations (word embeddings) which are then put in context in the hidden layers. Since words are often ambiguous, representing ...
  • McNally, Louise, 1965-; Boleda, Gemma (Colloque de Syntaxe et Sémantique à Paris, 2004)
  • 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; 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 ...
  • 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 ...
  • Corral, Álvaro; Boleda, Gemma; Ferrer-i-Cancho, Ramon (Public Library of Science (PLoS), 2015)
    Zipf’s law is a fundamental paradigm in the statistics of written and spoken natural language as well as in other communication systems. We raise the question of the elementary units for which Zipf’s law should hold in the ...