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Workshop on Evaluating Vector Space Representations for NLP 2016: all accepted papers

26 papers · the most cited first · ← Workshop on Evaluating Vector Space Representations for NLP 2016

  1. Problems With Evaluation of Word Embeddings Using Word Similarity TasksManaal Faruqui, Yulia Tsvetkov, Pushpendre Rastogi et al.246 citations · our summary
  2. Probing for semantic evidence of composition by means of simple classification tasksAllyson Ettinger, Ahmed Elgohary, Philip Resnik129 citations · our summary
  3. A critique of word similarity as a method for evaluating distributional semantic models ↗Miroslav Batchkarov, Thomas Kober, Jeremy Reffin et al.58 citations
  4. Evaluating Word Embeddings Using a Representative Suite of Practical Tasks ↗Neha Nayak Kennard, Gabor Angeli, Christopher D. Manning54 citations
  5. Story Cloze Evaluator: Vector Space Representation Evaluation by Predicting What Happens Next ↗Nasrin Mostafazadeh, Lucy Vanderwende, Wen-tau Yih et al.44 citations
  6. Correlation-based Intrinsic Evaluation of Word Vector Representations ↗Yulia Tsvetkov, Manaal Faruqui, Chris Dyer24 citations
  7. Thematic fit evaluation: an aspect of selectional preferences ↗Asad Sayeed, Clayton Greenberg, Vera Demberg22 citations
  8. Evaluation of acoustic word embeddings ↗Sahar Ghannay, Yannick Estève, Nathalie Camelin et al.10 citations
  9. Evaluating multi-sense embeddings for semantic resolution monolingually and in word translation ↗Gábor Borbély, Márton Makrai, Dávid Márk Nemeskey et al.4 citations
  10. Defining Words with Words: Beyond the Distributional Hypothesis ↗Iuliana-Elena Parasca, Andreas Lukas Rauter, Jack Roper et al.3 citations
  11. Sentence Embedding Evaluation Using Pyramid Annotation ↗Tal Baumel, Raphael Cohen, Michael Elhadad2 citations

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