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Distributional models provide a convenient way to model semantics using dense embedding spaces derived from unsupervised learning algorithms.
Learning effective and interpretable semantic models using non-negative sparse embedding
Brian Murphy, Partha Talukdar, and Tom Mitchell. 2012 · 1950
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Wordnet: a lexical database for english
George A Miller. 1995 · 1995
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Placing search in context: The concept revisited
Lev Finkelstein, Evgeniy Gabrilovich, Yossi Matias, Ehud Rivlin, Zach Solan, Gadi Wolfman, and Eytan Ruppin. 2001 · 2001
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Distributed and overlapping representations of faces and objects in ventral temporal cortex
James V Haxby, M Ida Gobbini, Maura L Furey, Alumit Ishai, Jennifer L Schouten, and Pietro Pietrini. 2001 · 2001
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Non-negative sparse coding
Patrik O Hoyer. 2002 · 2002
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Labeling images with a computer game
Luis Von Ahn and Laura Dabbish. 2004 · 2004
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Semantic feature production norms for a large set of living and nonliving things
Ken McRae, George S Cree, Mark S Seidenberg, and Chris McNorgan. 2005 · 2005
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Representational similarity analysis-connecting the branches of systems neuroscience
Nikolaus Kriegeskorte, Marieke Mur, and Peter A Bandettini. 2008 · 2008
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Predicting human brain activity associated with the meanings of nouns
Tom M Mitchell, Svetlana V Shinkareva, Andrew Carlson, Kai-Min Chang, Vicente L Malave, Robert A Mason, and Marcel Adam Just. 2008 · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009 · 2009
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Using fmri activation to conceptual stimuli to evaluate methods for extracting conceptual representations from corpora
Barry Devereux, Colin Kelly, and Anna Korhonen. 2010 · 2010
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Online learning for matrix factorization and sparse coding
Julien Mairal, Francis Bach, Jean Ponce, and Guillermo Sapiro. 2010 · 2010
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Multimodal deep learning
Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, and Andrew Y Ng. 2011 · 2011
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Distributional semantics in technicolor
Elia Bruni, Gemma Boleda, Marco Baroni, and Nam-Khanh Tran. 2012 · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
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Representational similarity analysis reveals commonalities and differences in the semantic processing of words and objects
Barry J Devereux, Alex Clarke, Andreas Marouchos, and Lorraine K Tyler. 2013 · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Visualizing and understanding convolutional networks
Matthew D. Zeiler and Rob Fergus. 2013 · 2013
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Multimodal distributional semantics
Elia Bruni, Nam-Khanh Tran, and Marco Baroni. 2014 · 2014
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Deep visual-semantic alignments for generating image descriptions
Andrej Karpathy and Fei-Fei Li. 2015 · 2015
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Combining language and vision with a multimodal skip-gram model
Angeliki Lazaridou, Nghia The Pham, and Marco Baroni. 2015 · 2015
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A critique of word similarity as a method for evaluating distributional semantic models
Miroslav Batchkarov, Thomas Kober, Jeremy Reffin, Julie Weeds, and David Weir. 2016 · 2016
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Is an image worth more than a thousand words? on the fine-grain semantic differences between visual and linguistic representations
Guillem Collell and Marie-Francine Moens. 2016 · 2016
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Intrinsic evaluations of word embeddings: What can we do better?
Anna Gladkova and Aleksandr Drozd. 2016 · 2016
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The centre for speech, language and the brain (cslb) concept property norms
Barry J Devereux, Lorraine K Tyler, Jeroen Geertzen, and Billi Randall. 2014 · 2014
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Interpretable semantic vectors from a joint model of brain-and text-based meaning
Alona Fyshe, Partha P Talukdar, Brian Murphy, and Tom M Mitchell. 2014 · 2014
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Learning image embeddings using convolutional neural networks for improved multi-modal semantics
Douwe Kiela and Léon Bottou. 2014 · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
Maxime Oquab, Leon Bottou, Ivan Laptev, and Josef Sivic. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Predicting the time course of individual objects with meg
Alex Clarke, Barry J. Devereux, Billi Randall, and Lorraine K. Tyler. 2015 · 2015
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Natural speech reveals the semantic maps that tile human cerebral cortex
Alexander G Huth, Wendy A de Heer, Thomas L Griffiths, Frédéric E Theunissen, and Jack L Gallant. 2016 · 2016
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Evaluating word embeddings with fmri and eye-tracking
Anders Søgaard. 2016 · 2016
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Imagined visual representations as multimodal embeddings
Guillem Collell, Ted Zhang, and Marie-Francine Moens. 2017 · 2017
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Li Lucy and Jon Gauthier. 2017 · 2017
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Semantic structure and interpretability of word embeddings
Lutfi Kerem Senel, Ihsan Utlu, Veysel Yucesoy, Aykut Koc, and Tolga Cukur. 2017 · 2017
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Visually grounded meaning representations
Carina Silberer, Vittorio Ferrari, and Mirella Lapata. 2017 · 2017
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Integrated deep visual and semantic attractor neural networks predict fmri pattern-information along the ventral object processing pathway
Barry J Devereux, Alex Clarke, and Lorraine K Tyler. 2018 · 2018
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Brainbench: A brain-image test suite for distributional semantic models
Haoyan Xu, Brian Murphy, and Alona Fyshe. 2016 · 2021
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