Google Scholar Profile

2016

  • Towards Multi-Agent Communication-Based Language Learning
    Angeliki Lazaridou, Nghia The Pham and Marco Baroni
    arxiv report
    paper
  • Multimodal word meaning induction from minimal exposure to natural text
    Angeliki Lazaridou, Marco Marelli and Marco Baroni
    Cognitive Science, to appear
    paper data
  • The red one!: On learning to refer to things based on their discriminative properties
    Angeliki Lazaridou, Nghia The Pham and Marco Baroni
    ACL 2016 Short, Oral
    paper
  • Multimodal semantic learning from child-directed input
    Angeliki Lazaridou, Grzegorz Chrupala, Raquel Fernandez and Marco Baroni
    NAACL 2016 Short
    paper
  • The LAMBADA dataset: Word prediction requiring a broad discourse context
    Denis Paperno, German Kruszewski, Angeliki Lazaridou, Quan Ngoc Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, Raquel Fernandez
    ACL2016 Long, Oral
    paper data
  • Look, some green circles!’’: Learning to quantify from images
    Ionut Sorodoc, Angeliki Lazaridou, Gemma Boleda, Aurélie Herbelot, Sandro Pezzelle and Raffaella Bernardi
    ACL2106, Vision and Language Workshop
    paper

2015

  • Unveiling the Dreams of Word Embeddings: Towards Language-Driven Image Generation
    Angeliki Lazaridou, Dat Tien Nguyen, Raffaela Bernardi and Marco Baroni
    Multimodal Machine Learning Workshop (NIPS 2016)
    paper
  • Do Distributed Semantic Models Dream of Electric Sheep? Visualizing Word Representations through Image Synthesis
    Angeliki Lazaridou, Dat Tien Nguyen and Marco Baroni
    VL 2015, co-located with EMNLP 2015, Long, Oral
    paper
  • Hubness and Pollution: Delving into Cross-Space Mapping for Zero-Shot Learning
    Angeliki Lazaridou, Georgiana Dinu and Marco Baroni
    ACL 2015 Long, Oral
    paper
  • From Visual Attributes to Adjectives through Decompositional Distributional Semantics
    Angeliki Lazaridou, Georgiana Dinu, Adam Liska and Marco Baroni
    Transactions of the Association for Computational Linguistics (TACL)
    paper
  • Combining Language and Vision with a Multimodal Skipgram Model
    Angeliki Lazaridou, Nghia The Pham and Marco Baroni
    NAACL 2015 Long, Oral (also appeared at NIPS Learning Semantics Workshop 2014)
    paper
  • Improving Zero-shot Learning by Mitigating the Hubness Problem
    Georgiana Dinu, Angeliki Lazaridou and Marco Baroni
    ICLR 2015, Workshop Track
    paper
  • A Multitask Objective to Inject Lexical Contrast into Distributional Semantics
    Nghia The Pham, Angeliki Lazaridou and Marco Baroni
    ACL 2015 Short, Oral
    paper
  • Jointly optimizing word representations for lexical and sentential tasks with the C-PHRASE model
    Nghia The Pham, German Kruzwewski, Angeliki Lazaridou and Marco Baroni
    ACL 2015 Long, Poster
    paper

2014

  • Is this a wampimuk? Cross-modal mapping between distributional semantics and the visual world
    Angeliki Lazaridou, Elia Bruni and Marco Baroni
    ACL 2014 Long, Oral
    paper slides talk
  • Coloring Objects: Adjective-Noun Visual Semantic Compositionality
    Dat Tien Nguyen, Angeliki Lazaridou and Raffaella Bernardi
    VL 2014, co-located with COLING 2014, Poster
    paper

2013

  • Compositional-ly derived representations of morphologically complex words in distributional semantics
    Angeliki Lazaridou, Marco Marelli, Roberto Zamparelli and Marco Baroni
    ACL 2013 Long, Oral
    paper data slides
  • A Bayesian Model for Joint Unsupervised Induction of Sentiment, Aspect and Discourse Representations
    Angeliki Lazaridou, Ivan Titov and Caroline Sporleder
    ACL 2013 Long, Oral
    paper data slides
  • Fish transporters and miracle homes: How compositional distributional semantics can help NP parsing
    Angeliki Lazaridou, Eva Maria Vecchi and Marco Baroni
    EMNLP 2013 Short, Oral
    paper data slides

2011

  • ELS: a word-level method for entity-level sentiment analysis
    Nikolaos Engonopoulos, Angeliki Lazaridou, Georgios Paliouras and Konstantinos Chandrinos
    WIMS 2011 Long, Oral
    paper