{"id":"https://openalex.org/W4220668513","doi":"https://doi.org/10.1145/3510580","title":"Improving Neural Machine Translation by Transferring Knowledge from Syntactic Constituent Alignment Learning","display_name":"Improving Neural Machine Translation by Transferring Knowledge from Syntactic Constituent Alignment Learning","publication_year":2022,"publication_date":"2022-03-23","ids":{"openalex":"https://openalex.org/W4220668513","doi":"https://doi.org/10.1145/3510580"},"language":"en","primary_location":{"id":"doi:10.1145/3510580","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3510580","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information 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/A5037571368","display_name":"Chao Su","orcid":"https://orcid.org/0000-0001-6771-329X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Su","raw_affiliation_strings":["Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6771-329X","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087631670","display_name":"Heyan Huang","orcid":"https://orcid.org/0000-0002-0320-7520"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyan Huang","raw_affiliation_strings":["Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0320-7520","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037738790","display_name":"Shumin Shi","orcid":"https://orcid.org/0000-0003-3436-7575"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shumin Shi","raw_affiliation_strings":["Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3436-7575","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101796595","display_name":"Ping Jian","orcid":"https://orcid.org/0000-0001-7236-2922"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Jian","raw_affiliation_strings":["Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7236-2922","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037571368"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.1387,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51558419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"21","issue":"5","first_page":"1","last_page":"15"},"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":0.9998000264167786,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9850999712944031,"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":0.8337879180908203},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.7523840665817261},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6980695724487305},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.6814554333686829},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6686174273490906},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6458699703216553},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.6023001074790955},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5868616104125977},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.5821496248245239},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5768871903419495},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5699508190155029},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.542003333568573},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5400271415710449},{"id":"https://openalex.org/keywords/example-based-machine-translation","display_name":"Example-based machine translation","score":0.5025873184204102},{"id":"https://openalex.org/keywords/word-order","display_name":"Word order","score":0.41105639934539795},{"id":"https://openalex.org/keywords/rule-based-machine-translation","display_name":"Rule-based machine translation","score":0.4101385176181793},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1328793466091156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8337879180908203},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.7523840665817261},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6980695724487305},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.6814554333686829},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6686174273490906},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6458699703216553},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.6023001074790955},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5868616104125977},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.5821496248245239},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5768871903419495},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5699508190155029},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.542003333568573},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5400271415710449},{"id":"https://openalex.org/C24687705","wikidata":"https://www.wikidata.org/wiki/Q3753284","display_name":"Example-based machine translation","level":3,"score":0.5025873184204102},{"id":"https://openalex.org/C70777604","wikidata":"https://www.wikidata.org/wiki/Q257885","display_name":"Word order","level":2,"score":0.41105639934539795},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.4101385176181793},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1328793466091156},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3510580","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3510580","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7200000286102295,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G5054543154","display_name":null,"funder_award_id":"61732005 and 61671064","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1524281572","https://openalex.org/W1593271688","https://openalex.org/W1965893653","https://openalex.org/W2097606805","https://openalex.org/W2112900913","https://openalex.org/W2124807415","https://openalex.org/W2133459682","https://openalex.org/W2146113428","https://openalex.org/W2152263452","https://openalex.org/W2157331557","https://openalex.org/W2560674852","https://openalex.org/W2594047108","https://openalex.org/W2612690371","https://openalex.org/W2739894144","https://openalex.org/W2741239863","https://openalex.org/W2798881773","https://openalex.org/W2803258077","https://openalex.org/W2884083742","https://openalex.org/W2889009749","https://openalex.org/W2889404673","https://openalex.org/W2930957955","https://openalex.org/W2948197522","https://openalex.org/W2949579048","https://openalex.org/W2962784628","https://openalex.org/W2962945603","https://openalex.org/W2962969034","https://openalex.org/W2963073938","https://openalex.org/W2963355447","https://openalex.org/W2963648186","https://openalex.org/W2963661253","https://openalex.org/W2963888305","https://openalex.org/W2964260331","https://openalex.org/W2964334713","https://openalex.org/W2982713930","https://openalex.org/W2983669550","https://openalex.org/W2998215494","https://openalex.org/W3106104873","https://openalex.org/W3106150792","https://openalex.org/W4235743066","https://openalex.org/W4241645538","https://openalex.org/W4365799947"],"related_works":["https://openalex.org/W193726211","https://openalex.org/W2566847733","https://openalex.org/W2122287718","https://openalex.org/W2010336863","https://openalex.org/W2740094425","https://openalex.org/W2587602790","https://openalex.org/W3011059803","https://openalex.org/W3204448004","https://openalex.org/W4378619223","https://openalex.org/W2809655258"],"abstract_inverted_index":{"Statistical":[0],"machine":[1,14],"translation":[2,15,126,134,166],"(SMT)":[3],"models":[4,17],"rely":[5],"on":[6,105],"word-,":[7],"phrase-,":[8],"and":[9,23,54,88,122,143,154],"syntax-level":[10,24],"alignments.":[11,25,41],"But":[12],"neural":[13],"(NMT)":[16],"rarely":[18],"explicitly":[19,35],"learn":[20,119],"the":[21,37,62,81,89,95,114,124,128,132,140,150,158,165],"phrase-":[22],"In":[26,110],"this":[27],"article,":[28],"we":[29,43,56],"propose":[30,57],"to":[31,48,60,76,79,92,118,138,144],"improve":[32,164],"NMT":[33],"by":[34],"learning":[36],"bilingual":[38],"syntactic":[39,46,50,63],"constituent":[40,120,160],"Specifically,":[42],"first":[44],"utilize":[45,61],"parsers":[47],"induce":[49],"structures":[51],"of":[52,84,97],"sentences,":[53],"then":[55],"two":[58],"ways":[59],"constituents":[64],"in":[65],"a":[66],"perceptual":[67],"(not":[68],"adversarial)":[69],"generator-discriminator":[70,112],"training":[71,86],"framework.":[72],"One":[73],"way":[74],"is":[75,91,116,136],"use":[77],"them":[78],"measure":[80],"alignment":[82,141],"score":[83,94],"sentence-level":[85],"examples,":[87],"other":[90],"directly":[93],"alignments":[96,107,121,161],"constituent-level":[98],"examples":[99],"generated":[100],"with":[101],"an":[102],"algorithm":[103],"based":[104],"word-level":[106],"from":[108,127],"SMT.":[109],"our":[111],"framework,":[113],"discriminator":[115],"pre-trained":[117],"distinguish":[123],"ground-truth":[125],"fake":[129],"ones,":[130],"while":[131],"generative":[133],"model":[135],"fine-tuned":[137],"receive":[139],"knowledge":[142],"generate":[145],"translations":[146],"that":[147,157],"best":[148],"approximate":[149],"true":[151],"ones.":[152],"Experiments":[153],"analysis":[155],"show":[156],"learned":[159],"can":[162],"help":[163],"results.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
