{"id":"https://openalex.org/W2965538726","doi":"https://doi.org/10.24963/ijcai.2019/746","title":"Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax","display_name":"Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2965538726","doi":"https://doi.org/10.24963/ijcai.2019/746","mag":"2965538726"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/746","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/746","pdf_url":"https://www.ijcai.org/proceedings/2019/0746.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0746.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112593580","display_name":"Yinfei Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yinfei Yang","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013110024","display_name":"Gustavo Hern\u00e1ndez \u00c1brego","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gustavo Hernandez Abrego","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057981124","display_name":"Steve Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steve Yuan","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004864409","display_name":"Mandy Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mandy Guo","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049185781","display_name":"Qinlan Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qinlan Shen","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073726152","display_name":"Daniel Cer","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Cer","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113807382","display_name":"Yun-Hsuan Sung","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun-hsuan Sung","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001487094","display_name":"Brian Strope","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Strope","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004215755","display_name":"Ray Kurzweil","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ray Kurzweil","raw_affiliation_strings":["Google AI Language"],"affiliations":[{"raw_affiliation_string":"Google AI Language","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5112593580"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":7.9564,"has_fulltext":true,"cited_by_count":82,"citation_normalized_percentile":{"value":0.97887128,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"5370","last_page":"5378"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","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/T13629","display_name":"Text Readability and Simplification","score":0.9753999710083008,"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/softmax-function","display_name":"Softmax function","score":0.9129116535186768},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.8172633647918701},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7920213937759399},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.7153537273406982},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7128463387489319},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6719386577606201},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6495842933654785},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6222094297409058},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5758717060089111},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5702105164527893},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5626808404922485},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5330290794372559},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5016191005706787},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3716442883014679},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3559751510620117},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.20107516646385193},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18530595302581787},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11029195785522461}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9129116535186768},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.8172633647918701},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7920213937759399},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.7153537273406982},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7128463387489319},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6719386577606201},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6495842933654785},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6222094297409058},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5758717060089111},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5702105164527893},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5626808404922485},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5330290794372559},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5016191005706787},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3716442883014679},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3559751510620117},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.20107516646385193},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18530595302581787},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11029195785522461},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/746","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/746","pdf_url":"https://www.ijcai.org/proceedings/2019/0746.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/746","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/746","pdf_url":"https://www.ijcai.org/proceedings/2019/0746.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965538726.pdf","grobid_xml":"https://content.openalex.org/works/W2965538726.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W145107721","https://openalex.org/W200075660","https://openalex.org/W2087735403","https://openalex.org/W2101096097","https://openalex.org/W2107695330","https://openalex.org/W2121879602","https://openalex.org/W2123675427","https://openalex.org/W2140903445","https://openalex.org/W2145080939","https://openalex.org/W2145251161","https://openalex.org/W2166098990","https://openalex.org/W2211192759","https://openalex.org/W2250929565","https://openalex.org/W2251994258","https://openalex.org/W2264105282","https://openalex.org/W2308899597","https://openalex.org/W2320039153","https://openalex.org/W2572474373","https://openalex.org/W2759183967","https://openalex.org/W2794365787","https://openalex.org/W2798389157","https://openalex.org/W2798583685","https://openalex.org/W2886198413","https://openalex.org/W2896457183","https://openalex.org/W2899099596","https://openalex.org/W2962735107","https://openalex.org/W2962890089","https://openalex.org/W2963149412","https://openalex.org/W2970618241","https://openalex.org/W3103152812","https://openalex.org/W4206856021","https://openalex.org/W4385245566","https://openalex.org/W6662462842","https://openalex.org/W6680812342","https://openalex.org/W6755742619","https://openalex.org/W6756680516","https://openalex.org/W6864014924"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W2982889384","https://openalex.org/W4226227567","https://openalex.org/W2971218105","https://openalex.org/W3010284783","https://openalex.org/W4287113729","https://openalex.org/W3173314472","https://openalex.org/W3103152812","https://openalex.org/W2947728370","https://openalex.org/W2268150819"],"abstract_inverted_index":{"In":[0,37],"this":[1,139],"paper,":[2],"we":[3,101,132],"present":[4],"an":[5],"approach":[6,56],"to":[7,24,57,65,123],"learn":[8],"multilingual":[9],"sentence":[10,80],"embeddings":[11,21,75,89,113],"using":[12],"a":[13,129,134],"bi-directional":[14],"dual-encoder":[15],"with":[16,114,128],"additive":[17],"margin":[18],"softmax.":[19],"The":[20,111],"are":[22],"able":[23],"achieve":[25,62,90,119,133],"state-of-the-art":[26,125,136],"results":[27,121],"on":[28,68,93,106,138],"the":[29,39,42,83,103,107],"United":[30],"Nations":[31],"(UN)":[32],"parallel":[33],"corpus":[34],"retrieval":[35,86],"task.":[36,110,140],"all":[38,96],"languages":[40],"tested,":[41],"system":[43],"achieves":[44],"P@1":[45,94],"of":[46],"86%":[47],"or":[48],"higher.":[49],"We":[50,71],"use":[51],"pairs":[52],"retrieved":[53],"by":[54,77],"our":[55,79],"train":[58],"NMT":[59],"models":[60,66],"that":[61],"similar":[63],"performance":[64],"trained":[67],"gold":[69],"pairs.":[70,99],"explore":[72],"simple":[73],"document-level":[74,85],"constructed":[76],"averaging":[78],"embeddings.":[81],"On":[82],"UN":[84],"task,":[87],"document":[88],"around":[91],"97%":[92],"for":[95],"experimented":[97],"language":[98],"Lastly,":[100],"evaluate":[102],"proposed":[104],"model":[105],"BUCC":[108],"mining":[109],"learned":[112],"raw":[115],"cosine":[116],"similarity":[117],"scores":[118],"competitive":[120],"compared":[122],"current":[124],"models,":[126],"and":[127],"second-stage":[130],"scorer":[131],"new":[135],"level":[137]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}