{"id":"https://openalex.org/W2901277442","doi":"https://doi.org/10.1109/icpr.2018.8546053","title":"Unsupervised Domain Adaptation for Neural Machine Translation","display_name":"Unsupervised Domain Adaptation for Neural Machine Translation","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2901277442","doi":"https://doi.org/10.1109/icpr.2018.8546053","mag":"2901277442"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8546053","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5084415556","display_name":"Zhen Yang","orcid":"https://orcid.org/0000-0002-7728-916X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Yang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344294","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0001-5090-9915"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431127","display_name":"Feng Wang","orcid":"https://orcid.org/0000-0001-6975-4335"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022604762","display_name":"Bo Xu","orcid":"https://orcid.org/0000-0003-4135-0683"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Xu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"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":0.9998000264167786,"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":0.9998000264167786,"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":0.996999979019165,"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":0.9726999998092651,"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/discriminator","display_name":"Discriminator","score":0.9490456581115723},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8071158528327942},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.7590993642807007},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6823052167892456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6768907308578491},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.668188750743866},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5751590728759766},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5436018109321594},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4926181435585022},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.4857078492641449},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4619249701499939},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34443461894989014},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.09429782629013062}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9490456581115723},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8071158528327942},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.7590993642807007},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6823052167892456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6768907308578491},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.668188750743866},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5751590728759766},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5436018109321594},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4926181435585022},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.4857078492641449},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4619249701499939},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34443461894989014},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.09429782629013062},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8546053","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8546053","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1753482797","https://openalex.org/W1836465849","https://openalex.org/W2101105183","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2176263492","https://openalex.org/W2271840356","https://openalex.org/W2523469089","https://openalex.org/W2525778437","https://openalex.org/W2550821151","https://openalex.org/W2567571499","https://openalex.org/W2572549015","https://openalex.org/W2579496717","https://openalex.org/W2581863816","https://openalex.org/W2584009249","https://openalex.org/W2601324753","https://openalex.org/W2610245951","https://openalex.org/W2610850660","https://openalex.org/W2611862713","https://openalex.org/W2613904329","https://openalex.org/W2626778328","https://openalex.org/W2741239878","https://openalex.org/W2949117887","https://openalex.org/W2949212125","https://openalex.org/W2952030765","https://openalex.org/W2963122608","https://openalex.org/W2963248296","https://openalex.org/W2963331137","https://openalex.org/W2963463964","https://openalex.org/W2963992143","https://openalex.org/W2964007535","https://openalex.org/W2964199361","https://openalex.org/W2964265128","https://openalex.org/W2964268978","https://openalex.org/W2964308564","https://openalex.org/W3037567775","https://openalex.org/W3098341425","https://openalex.org/W4385245566","https://openalex.org/W6679436768","https://openalex.org/W6685322675","https://openalex.org/W6731890338","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2898767136","https://openalex.org/W2756978580","https://openalex.org/W4283211831","https://openalex.org/W2740361506","https://openalex.org/W2798287483","https://openalex.org/W2963261224","https://openalex.org/W2577063019"],"abstract_inverted_index":{"Impressive":[0],"neural":[1],"machine":[2],"translation":[3,77,89,114,142],"(NMT)":[4],"results":[5,145],"are":[6,72,91,107],"achieved":[7],"in":[8,59,96,153],"domains":[9],"with":[10,23,109],"large-scale,":[11],"high":[12],"quality":[13],"bilingual":[14,29],"training":[15,30,49],"corpora.":[16],"However,":[17],"transferring":[18],"to":[19,53,74,120,126],"a":[20,46],"target":[21,60,97],"domain":[22,25,42,67,80,155],"significant":[24],"shifts":[26],"but":[27],"no":[28],"corpora":[31],"remains":[32],"largely":[33],"unexplored.":[34],"To":[35],"address":[36],"the":[37,55,66,76,84,88,94,104,110,121,132],"aforementioned":[38],"setting":[39],"of":[40],"unsupervised":[41,154],"adaptation,":[43],"we":[44],"propose":[45],"novel":[47],"adversarial":[48],"procedure":[50],"for":[51,157],"NMT":[52],"leverage":[54],"widespread":[56],"monolingual":[57],"data":[58],"domain.":[61,98],"Two":[62],"discriminative":[63],"networks,":[64],"namely":[65],"discriminator":[68,81,101],"and":[69,140],"pair":[70,100],"discriminator,":[71],"introduced":[73],"guide":[75],"model.":[78],"The":[79,99,113],"evaluates":[82],"whether":[83,103],"sentences":[85,106,128],"generated":[86,105],"by":[87,131],"model":[90,115],"indistinguishable":[92],"from":[93],"ones":[95],"assesses":[102],"paired":[108],"source-side":[111],"sentences.":[112],"acts":[116],"as":[117],"an":[118],"adversary":[119],"two":[122],"discriminators,":[123],"which":[124],"aims":[125],"generate":[127],"uneasily":[129],"discriminated":[130],"discriminators.":[133],"We":[134],"tested":[135],"our":[136,148],"approach":[137],"on":[138],"Chinese-English":[139],"English-German":[141],"tasks.":[143],"Experimental":[144],"show":[146],"that":[147],"approaches":[149],"achieve":[150],"great":[151],"success":[152],"adaptation":[156],"NMT.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}