{"id":"https://openalex.org/W2962379838","doi":"https://doi.org/10.1109/taslp.2019.2921423","title":"Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation","display_name":"Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation","publication_year":2019,"publication_date":"2019-06-06","ids":{"openalex":"https://openalex.org/W2962379838","doi":"https://doi.org/10.1109/taslp.2019.2921423","mag":"2962379838"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2019.2921423","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2019.2921423","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100713692","display_name":"Yijun Wang","orcid":"https://orcid.org/0000-0002-3372-8167"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yijun Wang","raw_affiliation_strings":["Anhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021772140","display_name":"Yingce Xia","orcid":"https://orcid.org/0000-0001-9823-9033"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingce Xia","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052155290","display_name":"Li Zhao","orcid":"https://orcid.org/0000-0001-5095-3377"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhao","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101544241","display_name":"Jiang Bian","orcid":"https://orcid.org/0000-0002-9472-600X"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Bian","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020025718","display_name":"Tao Qin","orcid":"https://orcid.org/0000-0002-9095-0776"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Qin","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048237545","display_name":"Enhong Chen","orcid":"https://orcid.org/0000-0002-4835-4102"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enhong Chen","raw_affiliation_strings":["Anhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101884287","display_name":"Tie\u2010Yan Liu","orcid":"https://orcid.org/0000-0002-0476-8020"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tie-Yan Liu","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100713692"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":1.1201,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.83690815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"27","issue":"10","first_page":"1564","last_page":"1576"},"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":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/computer-science","display_name":"Computer science","score":0.842795729637146},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.7269949316978455},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7161046266555786},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6675488352775574},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.648604154586792},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5869205594062805},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5168572068214417},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.515521764755249},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35543420910835266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.842795729637146},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.7269949316978455},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7161046266555786},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6675488352775574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.648604154586792},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5869205594062805},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5168572068214417},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.515521764755249},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35543420910835266},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2019.2921423","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2019.2921423","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.49000000953674316,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1064288964","display_name":null,"funder_award_id":"61727809","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G333974875","display_name":null,"funder_award_id":"2016YFB1000904","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5007750573","display_name":null,"funder_award_id":"U1605251","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":88,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W179875071","https://openalex.org/W1522301498","https://openalex.org/W1591801644","https://openalex.org/W1815076433","https://openalex.org/W1902237438","https://openalex.org/W1915251500","https://openalex.org/W1991522508","https://openalex.org/W2055423828","https://openalex.org/W2100664567","https://openalex.org/W2101105183","https://openalex.org/W2108501770","https://openalex.org/W2122270629","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2136156618","https://openalex.org/W2176263492","https://openalex.org/W2184135559","https://openalex.org/W2194775991","https://openalex.org/W2252272516","https://openalex.org/W2402268235","https://openalex.org/W2487501366","https://openalex.org/W2525778437","https://openalex.org/W2540404261","https://openalex.org/W2546938941","https://openalex.org/W2555428947","https://openalex.org/W2561274697","https://openalex.org/W2566564022","https://openalex.org/W2594990650","https://openalex.org/W2613904329","https://openalex.org/W2758310181","https://openalex.org/W2785093437","https://openalex.org/W2888442053","https://openalex.org/W2888779557","https://openalex.org/W2889326796","https://openalex.org/W2904664992","https://openalex.org/W2933991146","https://openalex.org/W2949416428","https://openalex.org/W2962784628","https://openalex.org/W2963109507","https://openalex.org/W2963216553","https://openalex.org/W2963248296","https://openalex.org/W2963357083","https://openalex.org/W2963403868","https://openalex.org/W2963551569","https://openalex.org/W2963774520","https://openalex.org/W2963842982","https://openalex.org/W2963991316","https://openalex.org/W2964121744","https://openalex.org/W2964265128","https://openalex.org/W2964308564","https://openalex.org/W2964352247","https://openalex.org/W3041866211","https://openalex.org/W4242067627","https://openalex.org/W4287330004","https://openalex.org/W4301368689","https://openalex.org/W4385245566","https://openalex.org/W6600284362","https://openalex.org/W6607333740","https://openalex.org/W6631190155","https://openalex.org/W6635446068","https://openalex.org/W6638545294","https://openalex.org/W6638575559","https://openalex.org/W6640059789","https://openalex.org/W6675944832","https://openalex.org/W6679434410","https://openalex.org/W6679436768","https://openalex.org/W6679934243","https://openalex.org/W6685145238","https://openalex.org/W6685322675","https://openalex.org/W6686282164","https://openalex.org/W6691588051","https://openalex.org/W6713098461","https://openalex.org/W6722524744","https://openalex.org/W6727690538","https://openalex.org/W6729053843","https://openalex.org/W6729383884","https://openalex.org/W6730083651","https://openalex.org/W6730949058","https://openalex.org/W6737778391","https://openalex.org/W6739901393","https://openalex.org/W6740590407","https://openalex.org/W6743477263","https://openalex.org/W6748218325","https://openalex.org/W6748979873","https://openalex.org/W6757135789","https://openalex.org/W6780039898","https://openalex.org/W6845883598"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"Neural":[0],"machine":[1],"translation":[2,122,125],"(NMT)":[3],"heavily":[4],"relies":[5],"on":[6,167],"parallel":[7,15],"bilingual":[8],"corpora":[9,16,28],"for":[10,96],"training.":[11],"Since":[12],"large-scale,":[13],"high-quality":[14],"are":[17,91],"usually":[18],"costly":[19],"to":[20,25,29,49,59,65,127,148],"collect,":[21],"it":[22],"is":[23,88],"appealing":[24],"exploit":[26,67],"monolingual":[27,47,79,99,163],"improve":[30],"NMT.":[31],"Inspired":[32],"by":[33,118],"the":[34,41,50,60,72,103,106,120,150],"law":[35,151],"of":[36,43,53,75,85,105,152,162],"total":[37,153],"probability,":[38,154],"which":[39],"connects":[40],"probability":[42,52,108],"a":[44,56,97],"given":[45,109],"target-side":[46],"sentence":[48,58,100],"conditional":[51,107],"translating":[54],"from":[55],"source":[57,94,112,140],"target":[61,98],"one,":[62],"we":[63,143],"propose":[64,144],"explicitly":[66],"this":[68,86,116],"connection":[69],"and":[70,134,159,169],"help":[71],"training":[73],"procedure":[74],"NMT":[76],"models":[77],"using":[78],"data.":[80],"The":[81],"key":[82],"technical":[83],"challenge":[84,117],"approach":[87],"that":[89,173],"there":[90],"exponentially":[92],"many":[93],"sentences":[95,133],"while":[101],"computing":[102],"sum":[104],"each":[110],"possible":[111,138],"sentence.":[113],"We":[114],"address":[115],"leveraging":[119],"reverse":[121],"model":[123],"(target-to-source":[124],"model)":[126],"sample":[128],"several":[129,180],"mostly":[130],"likely":[131],"source-side":[132],"avoid":[135],"enumerating":[136],"all":[137],"candidate":[139],"sentences.":[141],"Then":[142],"two":[145],"different":[146],"methods":[147,175],"leverage":[149],"including":[155],"marginal":[156],"distribution":[157],"regularization":[158],"likelihood":[160],"maximization":[161],"corpora.":[164],"Experiment":[165],"results":[166],"English-French":[168],"German-English":[170],"tasks":[171],"demonstrate":[172],"our":[174],"achieve":[176],"significant":[177],"improvement":[178],"over":[179],"strong":[181],"baselines.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}