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Semantic Data Set Construction from Human Clustering and Spatial Arrangement
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In: Computational Linguistics, Vol 47, Iss 1, Pp 69-116 (2021) (2021)
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| 2 |
Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages
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In: Transactions of the Association for Computational Linguistics, Vol 9, Pp 410-428 (2021) (2021)
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| 3 |
Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity
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In: Computational Linguistics, Vol 46, Iss 4, Pp 847-897 (2020) (2020)
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Improving Multi-Modal Representations Using Image Dispersion: Why Less is Sometimes More
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In: http://aclweb.org/anthology/P/P14/P14-2135.pdf (2014)
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| 5 |
Author manuscript, published in "COLING 2012, Mumbai: India (2012)" Multi-way Tensor Factorization for Unsupervised Lexical Acquisition
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In: http://hal.inria.fr/docs/00/78/37/11/PDF/VandeCruysEtAl2012Multi.pdf (2013)
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| 6 |
Learning syntactic verb frames using graphical models
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In: http://www.cl.cam.ac.uk/~do242/Papers/acl12_verb_frames.pdf (2012)
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| 7 |
Author manuscript, published in "Empirical Methods in Natural Language Processing, France (2011)" Latent Vector Weighting for Word Meaning in Context
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In: http://halshs.archives-ouvertes.fr/docs/00/66/64/75/PDF/D11-1094_3_.pdf (2012)
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| 8 |
Statistical metaphor processing
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In: http://wing.comp.nus.edu.sg/~antho/J/J13/J13-2003.pdf (2012)
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| 9 |
Learning syntactic verb frames using graphical models
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In: http://www.aclweb.org/anthology-new/P/P12/P12-1044.pdf (2012)
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| 10 |
Multi-way tensor factorization for unsupervised lexical acquisition
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In: http://aclweb.org/anthology/C/C12/C12-1165.pdf (2012)
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| 11 |
Document and corpus level inference for unsupervised and transductive learning of information structure of scientic documents
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In: http://aclweb.org/anthology/C/C12/C12-2097.pdf (2012)
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| 12 |
Exploring variation across biomedical subdomains
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In: http://www.cl.cam.ac.uk/~do242/Papers/coling10_domain_final.pdf (2010)
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Abstract:
Previous research has demonstrated the importance of handling differences between domains such as “newswire ” and “biomedicine ” when porting NLP systems from one domain to another. In this paper we identify the related issue of subdomain variation, i.e., differences between subsets of a domain that might be expected to behave homogeneously. Using a large corpus of research articles, we explore how subdomains of biomedicine vary across a variety of linguistic dimensions and discover that there is rich variation. We conclude that an awareness of such variation is necessary when deploying NLP systems for use in single or multiple subdomains. 1
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.422.160
http://www.cl.cam.ac.uk/~do242/Papers/coling10_domain_final.pdf
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| 13 |
Investigating the cross-linguistic potential of VerbNet-style classification
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In: http://halshs.archives-ouvertes.fr/docs/00/53/90/36/PDF/report-camera-ready.pdf (2010)
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| 14 |
Exploring variation across biomedical subdomains
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In: http://aclweb.org/anthology/C/C10/C10-1078.pdf (2010)
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| 15 |
LexSchem: A large subcategorization lexicon for French verbs
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In: http://lipn.univ-paris13.fr/~messiant/publications/messiant-lrec08.pdf (2008)
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| 16 |
A large-scale classification of English verbs
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In: http://verbs.colorado.edu/~kipper/Papers/lrec-journal.pdf (2008)
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| 17 |
The choice of features for classification of verbs in biomedical texts
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In: http://www.aclweb.org/anthology-new/C/C08/C08-1057.pdf (2008)
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| 18 |
Verb class discovery from rich syntactic data
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In: http://www.cl.cam.ac.uk/users/alk23/cicling-08.pdf (2008)
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| 19 |
Verb class discovery from rich syntactic data
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In: http://www.cl.cam.ac.uk/%7Els418/works/cicling08.pdf (2008)
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| 20 |
Automatic classification of verbs in biomedical texts
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In: http://www.cl.cam.ac.uk/users/alk23/korhonen-acl-06.pdf (2006)
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