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Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning
Alona Fyshe
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Partha P. Talukdar
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Brian Murphy
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Tom M. Mitchell
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Paper Details:
Month: June
Year: 2014
Location: Baltimore, Maryland
Venue:
ACL |
Citations
URL
Rotated Word Vector Representations and their Interpretability
Sungjoon Park
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JinYeong Bak
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Alice Oh
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Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge
Steven Derby
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Paul Miller
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Brian Murphy
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Barry Devereux
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Combining Language and Vision with a Multimodal Skip-gram Model
Angeliki Lazaridou
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Nghia The Pham
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Marco Baroni
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Sparse Overcomplete Word Vector Representations
Manaal Faruqui
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Yulia Tsvetkov
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Dani Yogatama
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Chris Dyer
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Noah A. Smith
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Non-distributional Word Vector Representations
Manaal Faruqui
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Chris Dyer
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Visually Grounded and Textual Semantic Models Differentially Decode Brain Activity Associated with Concrete and Abstract Nouns
Andrew J. Anderson
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Douwe Kiela
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Stephen Clark
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Massimo Poesio
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A Hybrid Distributional and Knowledge-based Model of Lexical Semantics
Nikolaos Aletras
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Mark Stevenson
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Sparsifying Word Representations for Deep Unordered Sentence Modeling
Prasanna Sattigeri
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Jayaraman J. Thiagarajan
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http://www.cs.cmu.edu/
http://spams-devel.gforge.inria.fr/
http://www.cs.cmu
http://www.cs.cmu.edu/
http://www.cs
Field Of Study
Linguistic Trends
Distributional Semantics
Embeddings
Approach
Discriminative Model
Dataset
Social Media
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