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Word embeddings are real-valued word representations able to capture lexical semantics and trained on natural language corpora.
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Modeling the influence of thematic fit (and other constraints) in on-line sentence comprehension
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Introduction to the conll-2000 shared task: Chunking
Tjong Kim Sang, E. F. and Buchholz, S. (2000) · 2000
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Integrating verbs, situation schemas, and thematic role concepts
Ferretti, T. R., McRae, K., and Hatherell, A. (2001) · 2001
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Placing search in context: The concept revisited
Finkelstein, L., Gabrilovich, E., Matias, Y., Rivlin, E., Solan, Z., Wolfman, G., and Ruppin, E. (2001) · 2001
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Mining the web for synonyms: Pmi-ir versus lsa on toefl
Turney, P. (2001) · 2001
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Roget’s thesaurus and semantic similarity
Jarmasz, M. and Szpakowicz, S. (2004) · 2003
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Introduction to the conll-2003 shared task: Language-independent named entity recognition
Tjong Kim Sang, E. F. and De Meulder, F. (2003) · 2003
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Feature-rich part-of-speech tagging with a cyclic dependency network
Toutanova, K., Klein, D., Manning, C. D., and Singer, Y. (2003) · 2003
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Combining independent modules to solve multiple-choice synonym and analogy problems
Turney, P. D., Littman, M. L., Bigham, J., and Shnayder, V. (2003) · 2003
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A distributional model of semantic context effects in lexical processing
McDonald, S. and Brew, C. (2004) · 2004
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Automatically constructing a corpus of sentential paraphrases
Dolan, W. B. and Brockett, C. (2005) · 2005
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The proposition bank: An annotated corpus of semantic roles
Palmer, M., Gildea, D., and Kingsbury, P. (2005) · 2005
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Attributes in lexical acquisition
Almuhareb, A. (2006) · 2006
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High-dimensional semantic space accounts of priming
Jones, M. N., Kintsch, W., and Mewhort, D. J. (2006) · 2006
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Verb similarity on the taxonomy of wordnet
Yang, D. and Powers, D. M. (2006) · 2006
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Computing semantic relatedness using wikipedia-based explicit semantic analysis
Gabrilovich, E. and Markovitch, S. (2007) · 2007
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Topics in semantic representation
Griffiths, T. L., Steyvers, M., and Tenenbaum, J. B. (2007) · 2007
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Dependency-based construction of semantic space models
Padó, S. and Lapata, M. (2007) · 2007
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The integration of syntax and semantic plausibility in a wide-coverage model of human sentence processing
Padó, U. (2007) · 2007
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Esslli 2008 workshop on distributional lexical semantics
Baroni, M., Evert, S., and Lenci, A. (2008) · 2008
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Distributional semantics in linguistic and cognitive research
Lenci, A. (2008) · 2008
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The latent relation mapping engine: Algorithm and experiments
Turney, P. D. (2008) · 2008
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A study on similarity and relatedness using distributional and wordnet-based approaches
Agirre, E., Alfonseca, E., Hall, K., Kravalova, J., Paşca, M., and Soroa, A. (2009) · 2009
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Consistency and variability in functional localisers
Duncan, K. J., Pattamadilok, C., Knierim, I., and Devlin, J. T. (2009) · 2009
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Measuring semantic relatedness with vector space models and random walks
Herdağdelen, A., Erk, K., and Baroni, M. (2009) · 2009
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A robust and extensible exemplar-based model of thematic fit
Vandekerckhove, B., Sandra, D., and Daelemans, W. (2009) · 2009
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Distributional memory: A general framework for corpus-based semantics
Baroni, M. and Lenci, A. (2010) · 2010
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Strudel: A corpus-based semantic model based on properties and types
Baroni, M., Murphy, B., Barbu, E., and Poesio, M. (2010) · 2010
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Multi-prototype vector-space models of word meaning
Reisinger, J. and Mooney, R. J. (2010) · 2010
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Word representations: a simple and general method for semi-supervised learning
Turian, J., Ratinov, L., and Bengio, Y. (2010) · 2010
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From frequency to meaning: Vector space models of semantics
Turney, P. D. and Pantel, P. (2010) · 2010
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How we blessed distributional semantic evaluation
Baroni, M. and Lenci, A. (2011) · 2011
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Natural language processing (almost) from scratch
Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., and Kuksa, P. (2011) · 2011
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Thirty years and counting: finding meaning in the n400 component of the event-related brain potential (erp)
Kutas, M. and Federmeier, K. D. (2011) · 2011
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Learning word vectors for sentiment analysis
Maas, A. L., Daly, R. E., Pham, P. T., Huang, D., Ng, A. Y., and Potts, C. (2011) · 2011
Find the word that does not belong: A framework for an intrinsic evaluation of word vector representations
Camacho-Collados, J. and Navigli, R. (2016) · 2016
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Intrinsic evaluation of word vectors fails to predict extrinsic performance
Chiu, B., Korhonen, A., and Pyysalo, S. (2016) · 2016
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What do you know about an alligator when you know the company it keeps?
Erk, K. (2016) · 2016
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Probing for semantic evidence of composition by means of simple classification tasks
Ettinger, A., Elgohary, A., and Resnik, P. (2016a) · 2016
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Evaluating vector space models using human semantic priming results
Ettinger, A. and Linzen, T. (2016) · 2016
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Problems with evaluation of word embeddings using word similarity tasks
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Computational methods to extract meaning from text and advance theories of human cognition
McNamara, D. S. (2011) · 2011
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Using language models and latent semantic analysis to characterise the n400m neural response
Parviz, M., Johnson, M., Johnson, B., and Brock, J. (2011) · 2011
Cited alongside, same era.
A word at a time: computing word relatedness using temporal semantic analysis
Radinsky, K., Agichtein, E., Gabrilovich, E., and Markovitch, S. (2011) · 2011
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Large-scale learning of word relatedness with constraints
Halawi, G., Dror, G., Gabrilovich, E., and Koren, Y. (2012) · 2012
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Semeval-2012 task 2: Measuring degrees of relational similarity
Jurgens, D. A., Turney, P. D., Mohammad, S. M., and Holyoak, K. J. (2012) · 2012
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The semantic priming project
Hutchison, K. A., Balota, D. A., Neely, J. H., Cortese, M. J., Cohen-Shikora, E. R., Tse, C.-S., Yap, M. J., Bengson, J. J., Niemeyer, D., and Buchanan, E. (2013) · 2013
Cited alongside, same era.
Faruqui, M., Tsvetkov, Y., Rastogi, P., and Dyer, C. (2016) · 2016
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Simverb-3500: A large-scale evaluation set of verb similarity
Gerz, D., Vulić, I., Hill, F., Reichart, R., and Korhonen, A. (2016) · 2016
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Intrinsic evaluations of word embeddings: What can we do better?
Gladkova, A. and Drozd, A. (2016) · 2016
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Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn’t
Gladkova, A., Drozd, A., and Matsuoka, S. (2016) · 2016
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Finding non-arbitrary form-meaning systematicity using string-metric learning for kernel regression
Gutiérrez, E. D., Levy, R., and Bergen, B. (2016) · 2016
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Simlex-999: Evaluating semantic models with (genuine) similarity estimation
Hill, F., Reichart, R., and Korhonen, A. (2016) · 2016
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Natural speech reveals the semantic maps that tile human cerebral cortex
Huth, A. G., de Heer, W. A., Griffiths, T. L., Theunissen, F. E., and Gallant, J. L. (2016) · 2016
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Evaluating embeddings using syntax-based classification tasks as a proxy for parser performance
Köhn, A. (2016) · 2016
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Capturing discriminative attributes in a distributional space: Task proposal
Krebs, A. and Paperno, D. (2016) · 2016
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An improved crowdsourcing based evaluation technique for word embedding methods
Liza, F. F. and Grzes, M. (2016) · 2016
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A proposal for linguistic similarity datasets based on commonality lists
Milajevs, D. and Griffiths, S. (2016) · 2016
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Story cloze evaluator: Vector space representation evaluation by predicting what happens next
Mostafazadeh, N., Vanderwende, L., Yih, W.-t., Kohli, P., and Allen, J. (2016) · 2016
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Evaluating word embeddings using a representative suite of practical tasks
Nayak, N., Angeli, G., and Manning, C. D. (2016) · 2016
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A comparative evaluation of off-the-shelf distributed semantic representations for modelling behavioural data
Pereira, F., Gershman, S., Ritter, S., and Botvinick, M. (2016) · 2016
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Thematic fit evaluation: an aspect of selectional preferences
Sayeed, A., Greenberg, C., and Demberg, V. (2016) · 2016
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Evaluating word embeddings with fmri and eye-tracking
Søgaard, A. (2016) · 2016
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Cross-lingual models of word embeddings: An empirical comparison
Upadhyay, S., Faruqui, M., Dyer, C., and Roth, D. (2016) · 2016
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Abnar, S., Ahmed, R., Mijnheer, M., and Zuidema, W. (2017) · 2017
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Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks
Auguste, J., Rey, A., and Favre, B. (2017) · 2017
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Bakarov, A. and Gureenkova, O. (2017) · 2017
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Semeval-2017 task 2: Multilingual and cross-lingual semantic word similarity
Camacho-Collados, J., Pilehvar, M. T., Collier, N., and Navigli, R. (2017) · 2017
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Traversal-free word vector evaluation in analogy space
Che, X., Ring, N., Raschkowski, W., Yang, H., and Meinel, C. (2017) · 2017
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Presenting geco: An eyetracking corpus of monolingual and bilingual sentence reading
Cop, U., Dirix, N., Drieghe, D., and Duyck, W. (2017) · 2017
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Word embeddings quantify 100 years of gender and ethnic stereotypes
Garg, N., Schiebinger, L., Jurafsky, D., and Zou, J. (2017) · 2017
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Hypothesis testing based intrinsic evaluation of word embeddings
Gurnani, N. (2017) · 2017
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How to evaluate word embeddings? on importance of data efficiency and simple supervised tasks
Jastrzebski, S., Leśniak, D., and Czarnecki, W. M. (2017) · 2017
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An exploration of word embedding initialization in deep-learning tasks
Kocmi, T. and Bojar, O. (2017) · 2017
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Arbitrariness of linguistic sign questioned: correlation between word form and meaning in russian
Kutuzov, A. (2017) · 2017
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Distributional models of word meaning
Lenci, A. (2017) · 2017
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The provo corpus: A large eye-tracking corpus with predictability norms
Luke, S. G. and Christianson, K. (2017) · 2017
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Explaining human performance in psycholinguistic tasks with models of semantic similarity based on prediction and counting: A review and empirical validation
Mandera, P., Keuleers, E., and Brysbaert, M. (2017) · 2017
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Semantic structure and interpretability of word embeddings
Senel, L. K., Utlu, I., Yucesoy, V., Koc, A., and Cukur, T. (2017) · 2017
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Specializing word embeddings for similarity or relatedness
Kiela, D., Hill, F., and Clark, S. (2015) · 2048
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