{"id":"https://openalex.org/W2989156240","doi":"https://doi.org/10.18653/v1/k19-1031","title":"On the Relation between Position Information and Sentence Length in Neural Machine Translation","display_name":"On the Relation between Position Information and Sentence Length in Neural Machine Translation","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2989156240","doi":"https://doi.org/10.18653/v1/k19-1031","mag":"2989156240"},"language":"en","primary_location":{"id":"doi:10.18653/v1/k19-1031","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k19-1031","pdf_url":"https://www.aclweb.org/anthology/K19-1031.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 23rd Conference on Computational Natural Language Learning (CoNLL)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/K19-1031.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078277722","display_name":"Masato Neishi","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masato Neishi","raw_affiliation_strings":["The University of Tokyo"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102962259","display_name":"Naoki Yoshinaga","orcid":"https://orcid.org/0000-0002-2160-2604"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoki Yoshinaga","raw_affiliation_strings":["Institute of Industrial Science, the University of Tokyo"],"affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, the University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5078277722"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":3.931,"has_fulltext":true,"cited_by_count":43,"citation_normalized_percentile":{"value":0.95033921,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"328","last_page":"338"},"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":0.9994000196456909,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9739999771118164,"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/overfitting","display_name":"Overfitting","score":0.8097429275512695},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.768641471862793},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7558614015579224},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.721574068069458},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7104448676109314},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6727389097213745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.651329517364502},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.48460277915000916},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45913153886795044},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.43164151906967163},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3986871838569641},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.059116512537002563}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8097429275512695},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.768641471862793},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7558614015579224},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.721574068069458},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7104448676109314},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6727389097213745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.651329517364502},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.48460277915000916},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45913153886795044},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.43164151906967163},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3986871838569641},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.059116512537002563},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/k19-1031","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k19-1031","pdf_url":"https://www.aclweb.org/anthology/K19-1031.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 23rd Conference on Computational Natural Language Learning (CoNLL)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/k19-1031","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k19-1031","pdf_url":"https://www.aclweb.org/anthology/K19-1031.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 23rd Conference on Computational Natural Language Learning (CoNLL)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6200000047683716}],"awards":[],"funders":[{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2989156240.pdf","grobid_xml":"https://content.openalex.org/works/W2989156240.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1591706642","https://openalex.org/W1793121960","https://openalex.org/W1902237438","https://openalex.org/W2064675550","https://openalex.org/W2101105183","https://openalex.org/W2124807415","https://openalex.org/W2127863960","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2157331557","https://openalex.org/W2467173223","https://openalex.org/W2540404261","https://openalex.org/W2561386235","https://openalex.org/W2576482813","https://openalex.org/W2595715041","https://openalex.org/W2613904329","https://openalex.org/W2886845974","https://openalex.org/W2951008357","https://openalex.org/W2962965405","https://openalex.org/W2963174729","https://openalex.org/W2963250244","https://openalex.org/W2963403868","https://openalex.org/W2963506925","https://openalex.org/W2963925437","https://openalex.org/W2963929190","https://openalex.org/W2963963856","https://openalex.org/W2964045208","https://openalex.org/W2964121744","https://openalex.org/W2964265128","https://openalex.org/W2964308564","https://openalex.org/W2964345285","https://openalex.org/W4298960041","https://openalex.org/W4301368689","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W3176018525","https://openalex.org/W2903533908","https://openalex.org/W3026554633","https://openalex.org/W2903810591","https://openalex.org/W4289548192","https://openalex.org/W2888520903","https://openalex.org/W2963499882","https://openalex.org/W2903399267","https://openalex.org/W2949454572","https://openalex.org/W3098873988"],"abstract_inverted_index":{"Long":[0],"sentences":[1,41,139],"have":[2,22],"been":[3],"one":[4],"of":[5,53,57,85,110,122],"the":[6,19,25,30,44,54,63,81,100,144,161],"major":[7],"challenges":[8],"in":[9,38,143],"neural":[10],"machine":[11],"translation":[12,131],"(NMT).":[13],"Although":[14],"some":[15],"approaches":[16],"such":[17],"as":[18],"attention":[20],"mechanism":[21],"partially":[23],"remedied":[24],"problem,":[26],"we":[27,78,102],"found":[28],"that":[29,90,134,154],"current":[31],"standard":[32],"NMT":[33,59,86],"model,":[34],"Transformer,":[35],"has":[36],"difficulty":[37],"translating":[39,138],"long":[40],"compared":[42],"to":[43,71,160],"former":[45],"standard,":[46],"Recurrent":[47],"Neural":[48],"Network":[49],"(RNN)-based":[50],"model.":[51],"One":[52],"key":[55],"differences":[56],"these":[58],"models":[60],"is":[61,69,93],"how":[62],"model":[64,118],"handles":[65],"position":[66,82,92,136,156],"information":[67,83],"which":[68,105],"essential":[70],"process":[72],"sequential":[73],"data.":[74,146],"In":[75],"this":[76],"study,":[77],"focus":[79],"on":[80,125,149],"type":[84],"models,":[87],"and":[88,114,119,128],"hypothesize":[89],"relative":[91,135],"better":[94],"than":[95,141],"absolute":[96,155],"position.":[97],"To":[98],"examine":[99],"hypothesis,":[101],"propose":[103],"RNN-Transformer":[104],"replaces":[106],"positional":[107],"encoding":[108],"layer":[109],"Transformer":[111],"by":[112],"RNN,":[113],"then":[115],"compare":[116],"RNN-based":[117],"four":[120],"variants":[121],"Transformer.":[123],"Experiments":[124],"ASPEC":[126],"English-to-Japanese":[127],"WMT2014":[129],"Englishto-German":[130],"tasks":[132],"demonstrate":[133],"helps":[137],"longer":[140],"those":[142],"training":[145,151],"Further":[147],"experiments":[148],"length-controlled":[150],"data":[152],"reveal":[153],"actually":[157],"causes":[158],"overfitting":[159],"sentence":[162],"length.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}