{"id":"https://openalex.org/W2964345285","doi":"https://doi.org/10.18653/v1/p19-1426","title":"Bridging the Gap between Training and Inference for Neural Machine Translation","display_name":"Bridging the Gap between Training and Inference for Neural Machine Translation","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2964345285","doi":"https://doi.org/10.18653/v1/p19-1426","mag":"2964345285"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1426","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1426","pdf_url":"https://www.aclweb.org/anthology/P19-1426.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1426.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100448121","display_name":"Wen Zhang","orcid":"https://orcid.org/0000-0001-5221-2628"},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"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":true,"raw_author_name":"Wen Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS)","University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS)","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"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/A5000232528","display_name":"Yang Feng","orcid":null},"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/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"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":"Yang Feng","raw_affiliation_strings":["Key Laboratory of Intelligent Information Processing Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS)","University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Information Processing Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS)","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"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/A5024849044","display_name":"Fandong Meng","orcid":"https://orcid.org/0000-0002-8158-2377"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fandong Meng","raw_affiliation_strings":["Pattern Recognition Center, WeChat AI, Tencent Inc, China"],"affiliations":[{"raw_affiliation_string":"Pattern Recognition Center, WeChat AI, Tencent Inc, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101923296","display_name":"Di You","orcid":"https://orcid.org/0000-0003-3729-464X"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Di You","raw_affiliation_strings":["Worcester Polytechnic Institute, Worcester, MA, USA"],"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Worcester, MA, USA","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100426170","display_name":"Qun Liu","orcid":"https://orcid.org/0000-0002-7000-1792"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qun Liu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Hong Kong, China"],"affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Hong Kong, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100448121"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":23.4101,"has_fulltext":true,"cited_by_count":209,"citation_normalized_percentile":{"value":0.99574696,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4334","last_page":"4343"},"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":0.9926999807357788,"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/machine-translation","display_name":"Machine translation","score":0.839148998260498},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7996326684951782},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.6934021711349487},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6480216383934021},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6341812014579773},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6313878893852234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6211082935333252},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6125872135162354},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6106342077255249},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.604122519493103},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5563355684280396},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4490514397621155},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4466820955276489},{"id":"https://openalex.org/keywords/german","display_name":"German","score":0.446408212184906},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11941313743591309},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.11131343245506287}],"concepts":[{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.839148998260498},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7996326684951782},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.6934021711349487},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6480216383934021},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6341812014579773},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6313878893852234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6211082935333252},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6125872135162354},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6106342077255249},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.604122519493103},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5563355684280396},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4490514397621155},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4466820955276489},{"id":"https://openalex.org/C154775046","wikidata":"https://www.wikidata.org/wiki/Q188","display_name":"German","level":2,"score":0.446408212184906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11941313743591309},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11131343245506287},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1426","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1426","pdf_url":"https://www.aclweb.org/anthology/P19-1426.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1426","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1426","pdf_url":"https://www.aclweb.org/anthology/P19-1426.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6100000143051147}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G540065012","display_name":null,"funder_award_id":"61662077","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964345285.pdf","grobid_xml":"https://content.openalex.org/works/W2964345285.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W648786980","https://openalex.org/W2101105183","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2154652894","https://openalex.org/W2157331557","https://openalex.org/W2162245945","https://openalex.org/W2176263492","https://openalex.org/W2268617045","https://openalex.org/W2296701362","https://openalex.org/W2525778437","https://openalex.org/W2613904329","https://openalex.org/W2741986820","https://openalex.org/W2890220768","https://openalex.org/W2904829696","https://openalex.org/W2962784628","https://openalex.org/W2963260202","https://openalex.org/W2963403868","https://openalex.org/W2963463964","https://openalex.org/W2964265128","https://openalex.org/W2964308564","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4388870064","https://openalex.org/W4235186151","https://openalex.org/W2054685365","https://openalex.org/W2272354214","https://openalex.org/W2120383820","https://openalex.org/W2043010663","https://openalex.org/W2667588871","https://openalex.org/W4248308508","https://openalex.org/W118554674","https://openalex.org/W2757563118"],"abstract_inverted_index":{"Neural":[0],"Machine":[1],"Translation":[2],"(NMT)":[3],"generates":[4],"target":[5],"words":[6,30,92],"sequentially":[7],"in":[8],"the":[9,13,18,27,40,48,56,65,69,96,103,107,112],"way":[10],"of":[11,47],"predicting":[12],"next":[14],"word":[15],"conditioned":[16],"on":[17,123,138],"context":[19,32,50,91],"words.":[20],"At":[21],"training":[22,60],"time,":[23],"it":[24,36],"predicts":[25],"with":[26,117],"ground":[28,70,97],"truth":[29,71,98],"as":[31],"while":[33],"at":[34],"inference":[35],"has":[37],"to":[38,52,75],"generate":[39],"entire":[41],"sequence":[42,67,72,99,105,114],"from":[43,95,102],"scratch.":[44],"This":[45],"discrepancy":[46],"fed":[49],"leads":[51,74],"error":[53],"accumulation":[54],"among":[55],"way.":[57],"Furthermore,":[58],"word-level":[59],"requires":[61],"strict":[62],"matching":[63],"between":[64],"generated":[66],"and":[68,125],"which":[73],"overcorrection":[76],"over":[77],"different":[78],"but":[79,100],"reasonable":[80],"translations.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85],"address":[86],"these":[87],"issues":[88],"by":[89,106],"sampling":[90],"not":[93],"only":[94],"also":[101],"predicted":[104,113],"model":[108],"during":[109],"training,":[110],"where":[111],"is":[115],"selected":[116],"a":[118],"sentence-level":[119],"optimum.":[120],"Experiment":[121],"results":[122],"ChineseEnglish":[124],"WMT'14":[126],"EnglishGerman":[127],"translation":[128],"tasks":[129],"demonstrate":[130],"that":[131],"our":[132],"approach":[133],"can":[134],"achieve":[135],"significant":[136],"improvements":[137],"multiple":[139],"datasets.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":64},{"year":2020,"cited_by_count":57},{"year":2019,"cited_by_count":8}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
