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We generate concrete models for this setting by developing algorithms to construct tensors and linear maps and instantiate the abstract parameters using empirical data. We then evaluate our concrete models against several experiments, both existing and new, based on measuring how well models align with human judgments in a paraphrase detection task. Our results show the implementation of this general abstract framework to perform on par with or outperform other leading models in these experiments.<jats:sup>1<\/jats:sup><\/jats:p>","DOI":"10.1162\/coli_a_00209","type":"journal-article","created":{"date-parts":[[2015,2,23]],"date-time":"2015-02-23T15:11:01Z","timestamp":1424704261000},"page":"71-118","source":"Crossref","is-referenced-by-count":20,"title":["Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning"],"prefix":"10.1162","volume":"41","author":[{"given":"Edward","family":"Grefenstette","sequence":"first","affiliation":[{"name":"Google DeepMind"}]},{"given":"Mehrnoosh","family":"Sadrzadeh","sequence":"additional","affiliation":[{"name":"Queen Mary University of London"}]}],"member":"281","reference":[{"key":"R3","unstructured":"Baroni, M. and R. Zamparelli. 2010. Nouns are vectors, adjectives are matrices: Representing adjective-noun constructions in semantic space. 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