Browsing by Author "Pham, Nghia The"

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  • Convolutional neural network language models
    Boleda, Gemma; Pham, Nghia The; Kruszewski, German (ACL (Association for Computational Linguistics), 2016)
    Convolutional Neural Networks (CNNs) have shown to yield very strong results in several Computer Vision tasks. Their application to language has received much less attention, and it has mainly focused on static classification ...
  • Intensionality was only alleged: on adjective-noun composition in distributional semantics
    Boleda, Gemma; Baroni, Marco; Pham, Nghia The; McNally, Louise, 1965- (ACL (Association for Computational Linguistics), 2013)
    Distributional semantics has very successfully modeled semantic phenomena at the word level, and recently interest has grown in extending it to capture the meaning of phrases via semantic composition. We present experiments ...
  • Jointly optimizing word representations for lexical and sentential tasks with the C-PHRASE model
    Pham, Nghia The; Kruszewski, German; Lazaridou, Angeliki; Baroni, Marco (ACL (Association for Computational Linguistics), 2015)
    We introduce C-PHRASE, a distributional semantic model that learns word representations by optimizing context prediction for phrases at all levels in a syntactic tree, from single words to full sentences. C-PHRASE outperforms ...
  • Living a discrete life in a continuous world: reference with distributed representations
    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 ...
  • "The red one!": on learning to refer to things based on discriminative properties
    Lazaridou, Angeliki; Pham, Nghia The; Baroni, Marco (ACL (Association for Computational Linguistics), 2016)
    As a first step towards agents learning to communicate about their visual environment, we propose a system that, given visual representations of a referent (CAT) and a context (SOFA), identifies their discriminative ...