{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T06:08:28Z","timestamp":1774591708756,"version":"3.50.1"},"reference-count":16,"publisher":"MIT Press - Journals","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["TACL"],"published-print":{"date-parts":[[2017,12]]},"abstract":"<jats:p> We present Attract-Repel, an algorithm for improving the semantic quality of word vectors by injecting constraints extracted from lexical resources. Attract-Repel facilitates the use of constraints from mono- and cross-lingual resources, yielding semantically specialized cross-lingual vector spaces. Our evaluation shows that the method can make use of existing cross-lingual lexicons to construct high-quality vector spaces for a plethora of different languages, facilitating semantic transfer from high- to lower-resource ones. The effectiveness of our approach is demonstrated with state-of-the-art results on semantic similarity datasets in six languages. We next show that Attract-Repel-specialized vectors boost performance in the downstream task of dialogue state tracking (DST) across multiple languages. Finally, we show that cross-lingual vector spaces produced by our algorithm facilitate the training of multilingual DST models, which brings further performance improvements. <\/jats:p>","DOI":"10.1162\/tacl_a_00063","type":"journal-article","created":{"date-parts":[[2018,12,28]],"date-time":"2018-12-28T15:42:50Z","timestamp":1546011770000},"page":"309-324","source":"Crossref","is-referenced-by-count":48,"title":["Semantic Specialization of Distributional Word Vector Spaces using                     Monolingual and Cross-Lingual Constraints"],"prefix":"10.1162","volume":"5","author":[{"given":"Nikola","family":"Mrk\u0161i\u0107","sequence":"first","affiliation":[{"name":"University of Cambridge"},{"name":"Apple Inc."}]},{"given":"Ivan","family":"Vuli\u0107","sequence":"additional","affiliation":[{"name":"University of Cambridge"}]},{"given":"Diarmuid \u00d3","family":"S\u00e9aghdha","sequence":"additional","affiliation":[{"name":"Apple 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