{"id":"https://openalex.org/W2251855842","doi":"https://doi.org/10.3115/v1/p14-1011","title":"Bilingually-constrained Phrase Embeddings for Machine Translation","display_name":"Bilingually-constrained Phrase Embeddings for Machine Translation","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2251855842","doi":"https://doi.org/10.3115/v1/p14-1011","mag":"2251855842"},"language":"en","primary_location":{"id":"doi:10.3115/v1/p14-1011","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-1011","pdf_url":"https://aclanthology.org/P14-1011.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/P14-1011.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100319572","display_name":"Jiajun Zhang","orcid":"https://orcid.org/0000-0001-5293-7434"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Zhang","raw_affiliation_strings":["National Laboratory of Pattern Recognition, CASIA, Beijing, P.R. China","Institute of Automation. Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, CASIA, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210112150"]},{"raw_affiliation_string":"Institute of Automation. Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101635405","display_name":"Shujie Liu","orcid":"https://orcid.org/0009-0008-2599-6752"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shujie Liu","raw_affiliation_strings":["Microsoft Research Asia, Beijing, P.R. China","Institute of Automation. Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Institute of Automation. Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399466","display_name":"Mu Li","orcid":"https://orcid.org/0000-0002-7327-3304"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Mu Li","raw_affiliation_strings":["Microsoft Research Asia, Beijing, P.R. China","(Microsoft)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"(Microsoft)","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701572","display_name":"Ming Zhou","orcid":"https://orcid.org/0000-0002-2551-2964"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Ming Zhou","raw_affiliation_strings":["Microsoft Research Asia, Beijing, P.R. China","(Microsoft)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"(Microsoft)","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015785439","display_name":"Chengqing Zong","orcid":"https://orcid.org/0000-0002-9864-3818"},"institutions":[{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["CN","GB"],"is_corresponding":false,"raw_author_name":"Chengqing Zong","raw_affiliation_strings":["National Laboratory of Pattern Recognition, CASIA, Beijing, P.R. China","(Microsoft)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, CASIA, Beijing, P.R. China","institution_ids":["https://openalex.org/I4210112150"]},{"raw_affiliation_string":"(Microsoft)","institution_ids":["https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":123,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.8631654977798462},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8055155277252197},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7392568588256836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6934364438056946},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6555808782577515},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.576962411403656},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5727283954620361},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5521253943443298},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.47433632612228394},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.43171077966690063},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4308462142944336},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3804023861885071}],"concepts":[{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.8631654977798462},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8055155277252197},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7392568588256836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6934364438056946},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6555808782577515},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.576962411403656},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5727283954620361},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5521253943443298},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47433632612228394},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.43171077966690063},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4308462142944336},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3804023861885071},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3115/v1/p14-1011","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-1011","pdf_url":"https://aclanthology.org/P14-1011.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.654.1375","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.654.1375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/P/P14/P14-1011.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/p14-1011","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/p14-1011","pdf_url":"https://aclanthology.org/P14-1011.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6499999761581421,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2204133011","display_name":"\u6c49\u8bed\u591a\u5c42\u6b21\u8bed\u7bc7\u5206\u6790\u7406\u8bba\u65b9\u6cd5\u7814\u7a76\u4e0e\u5e94\u7528","funder_award_id":"61333018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3743304080","display_name":null,"funder_award_id":"61303181","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4243412236","display_name":null,"funder_award_id":"863 Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335773","display_name":"National High-tech Research and Development Program","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2251855842.pdf","grobid_xml":"https://content.openalex.org/works/W2251855842.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W71795751","https://openalex.org/W100623710","https://openalex.org/W132913264","https://openalex.org/W179875071","https://openalex.org/W222053410","https://openalex.org/W932413789","https://openalex.org/W1675954498","https://openalex.org/W1725104462","https://openalex.org/W1753482797","https://openalex.org/W2104518905","https://openalex.org/W2117130368","https://openalex.org/W2118090838","https://openalex.org/W2118536060","https://openalex.org/W2133280805","https://openalex.org/W2143269898","https://openalex.org/W2147262247","https://openalex.org/W2147768505","https://openalex.org/W2153579005","https://openalex.org/W2158388102","https://openalex.org/W2158899491","https://openalex.org/W2163605009","https://openalex.org/W2169488311","https://openalex.org/W2250489405","https://openalex.org/W2250714477","https://openalex.org/W2251395256","https://openalex.org/W2251690405","https://openalex.org/W2251939518","https://openalex.org/W2952230511","https://openalex.org/W2998704965","https://openalex.org/W3197700997","https://openalex.org/W3203497103","https://openalex.org/W4233906699","https://openalex.org/W4285719527","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W2039546652","https://openalex.org/W3011059803","https://openalex.org/W2012262991","https://openalex.org/W2373794620","https://openalex.org/W2373300491","https://openalex.org/W2384400852","https://openalex.org/W2963259630","https://openalex.org/W2070920720","https://openalex.org/W2398549619","https://openalex.org/W1542743110"],"abstract_inverted_index":{"We":[0,78],"propose":[1],"Bilingually-constrained":[2],"Recursive":[3],"Auto-encoders":[4],"(BRAE)":[5],"to":[6,55,67,75,99],"learn":[7],"semantic":[8,23,35,43,69,95,101],"phrase":[9,58,106],"embeddings":[10],"(compact":[11],"vector":[12],"representations":[13],"for":[14],"phrases),":[15],"which":[16,97],"can":[17],"distinguish":[18],"the":[19,34,42,51,76,115],"phrases":[20],"with":[21,93],"different":[22],"meanings.":[24],"The":[25],"BRAE":[26,116],"is":[27,117],"trained":[28],"in":[29,60,72,120],"a":[30,104],"way":[31],"that":[32,114],"minimizes":[33],"distance":[36,44],"of":[37,45],"translation":[38,109],"equivalents":[39],"and":[40,63,91,107],"maximizes":[41],"nontranslation":[46],"pairs":[47],"simultaneously.":[48],"After":[49],"training,":[50],"model":[52],"learns":[53,65],"how":[54,66],"embed":[56],"each":[57],"semantically":[59],"two":[61,84,122],"languages":[62],"also":[64],"transform":[68],"embedding":[70],"space":[71],"one":[73],"language":[74],"other.":[77],"evaluate":[79],"our":[80],"proposed":[81],"method":[82],"on":[83],"end-to-end":[85],"SMT":[86],"tasks":[87],"(phrase":[88],"table":[89],"pruning":[90],"decoding":[92],"phrasal":[94],"similarities)":[96],"need":[98],"measure":[100],"similarity":[102],"between":[103],"source":[105],"its":[108],"candidates.":[110],"Extensive":[111],"experiments":[112],"show":[113],"remarkably":[118],"effective":[119],"these":[121],"tasks.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":17},{"year":2016,"cited_by_count":25},{"year":2015,"cited_by_count":22},{"year":2014,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}