Workshop on Continuous Vector Space Models and their Compositionality (2013)
Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality
Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality
Alexandre Allauzen
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Hugo Larochelle
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Christopher Manning
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Richard Socher
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
Jayant Krishnamurthy
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Tom Mitchell
Learning from errors: Using vector-based compositional semantics for parse reranking
Phong Le
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Willem Zuidema
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Remko Scha
A Structured Distributional Semantic Model : Integrating Structure with Semantics
Kartik Goyal
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Sujay Kumar Jauhar
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Huiying Li
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Mrinmaya Sachan
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Shashank Srivastava
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Eduard Hovy
Letter N-Gram-based Input Encoding for Continuous Space Language Models
Henning Sperr
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Jan Niehues
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Alex Waibel
Transducing Sentences to Syntactic Feature Vectors: an Alternative Way to “Parse”?
Fabio Massimo Zanzotto
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Lorenzo Dell’Arciprete
General estimation and evaluation of compositional distributional semantic models
Georgiana Dinu
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Nghia The Pham
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Marco Baroni
Applicative structure in vector space models
Márton Makrai
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David Mark Nemeskey
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András Kornai
Determining Compositionality of Expresssions Using Various Word Space Models and Methods
Lubomír Krčmář
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Karel Ježek
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Pavel Pecina
“Not not bad” is not “bad”: A distributional account of negation
Karl Moritz Hermann
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Edward Grefenstette
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Phil Blunsom
Towards Dynamic Word Sense Discrimination with Random Indexing
Hans Moen
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Erwin Marsi
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Björn Gambäck
A Generative Model of Vector Space Semantics
Jacob Andreas
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Zoubin Ghahramani
Aggregating Continuous Word Embeddings for Information Retrieval
Stéphane Clinchant
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Florent Perronnin
Answer Extraction by Recursive Parse Tree Descent
Christopher Malon
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Bing Bai
Recurrent Convolutional Neural Networks for Discourse Compositionality
Nal Kalchbrenner
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Phil Blunsom