{"id":"https://openalex.org/W2950797315","doi":"https://doi.org/10.18653/v1/p19-1018","title":"Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces","display_name":"Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2950797315","doi":"https://doi.org/10.18653/v1/p19-1018","mag":"2950797315"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1018","pdf_url":"https://www.aclweb.org/anthology/P19-1018.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":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1018.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076387701","display_name":"Barun Patra","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Barun Patra","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000244424","display_name":"Joel Ruben Antony Moniz","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joel Ruben Antony Moniz","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021289729","display_name":"Sarthak Garg","orcid":"https://orcid.org/0000-0002-5030-0840"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sarthak Garg","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061241015","display_name":"Matthew R. Gormley","orcid":"https://orcid.org/0009-0002-7785-6045"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew R. Gormley","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068811427","display_name":"Graham Neubig","orcid":"https://orcid.org/0000-0002-2072-3789"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Graham Neubig","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5076387701"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":10.6927,"has_fulltext":true,"cited_by_count":104,"citation_normalized_percentile":{"value":0.98566284,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"184","last_page":"193"},"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":0.9998999834060669,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.9937999844551086,"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/lexicon","display_name":"Lexicon","score":0.7382591962814331},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7081676125526428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6918587684631348},{"id":"https://openalex.org/keywords/isometry","display_name":"Isometry (Riemannian geometry)","score":0.5177730321884155},{"id":"https://openalex.org/keywords/bliss","display_name":"BLISS","score":0.5133664011955261},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.49424245953559875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48658668994903564},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4827505946159363},{"id":"https://openalex.org/keywords/isometric-exercise","display_name":"Isometric exercise","score":0.4670179486274719},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43497148156166077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26784929633140564},{"id":"https://openalex.org/keywords/pure-mathematics","display_name":"Pure mathematics","score":0.1592983603477478}],"concepts":[{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.7382591962814331},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7081676125526428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6918587684631348},{"id":"https://openalex.org/C82457910","wikidata":"https://www.wikidata.org/wiki/Q740207","display_name":"Isometry (Riemannian geometry)","level":2,"score":0.5177730321884155},{"id":"https://openalex.org/C2780658912","wikidata":"https://www.wikidata.org/wiki/Q2877155","display_name":"BLISS","level":2,"score":0.5133664011955261},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.49424245953559875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48658668994903564},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4827505946159363},{"id":"https://openalex.org/C103486182","wikidata":"https://www.wikidata.org/wiki/Q1216236","display_name":"Isometric exercise","level":2,"score":0.4670179486274719},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43497148156166077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26784929633140564},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.1592983603477478},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1018","pdf_url":"https://www.aclweb.org/anthology/P19-1018.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/p19-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1018","pdf_url":"https://www.aclweb.org/anthology/P19-1018.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":[{"display_name":"Quality Education","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2950797315.pdf","grobid_xml":"https://content.openalex.org/works/W2950797315.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W342285082","https://openalex.org/W1508577659","https://openalex.org/W1542713999","https://openalex.org/W2108776879","https://openalex.org/W2118090838","https://openalex.org/W2126725946","https://openalex.org/W2140406733","https://openalex.org/W2153579005","https://openalex.org/W2157133710","https://openalex.org/W2171082019","https://openalex.org/W2250539671","https://openalex.org/W2251033195","https://openalex.org/W2251765408","https://openalex.org/W2294774419","https://openalex.org/W2471692228","https://openalex.org/W2493916176","https://openalex.org/W2561995736","https://openalex.org/W2578868202","https://openalex.org/W2626534681","https://openalex.org/W2740132093","https://openalex.org/W2741602058","https://openalex.org/W2760424551","https://openalex.org/W2785661498","https://openalex.org/W2788353357","https://openalex.org/W2888740011","https://openalex.org/W2890605385","https://openalex.org/W2891896107","https://openalex.org/W2952190837","https://openalex.org/W2962844668","https://openalex.org/W2963047628","https://openalex.org/W2963061446","https://openalex.org/W2963118869","https://openalex.org/W2963971961","https://openalex.org/W2964085268","https://openalex.org/W2964266061","https://openalex.org/W3010805239","https://openalex.org/W4211095002","https://openalex.org/W4294170691","https://openalex.org/W4299579390","https://openalex.org/W4302571896"],"related_works":["https://openalex.org/W2884598295","https://openalex.org/W2313933600","https://openalex.org/W2334720037","https://openalex.org/W2033249454","https://openalex.org/W2100847845","https://openalex.org/W2477081420","https://openalex.org/W3212259716","https://openalex.org/W2387715358","https://openalex.org/W2077583161","https://openalex.org/W2576018346"],"abstract_inverted_index":{"Recent":[0],"work":[1],"on":[2,11,16,111,117],"bilingual":[3,13,84],"lexicon":[4],"induction":[5],"(BLI)":[6],"has":[7],"frequently":[8],"depended":[9],"either":[10],"aligned":[12,83],"lexicons":[14,85],"or":[15],"distribution":[17],"matching,":[18],"often":[19],"with":[20,68,150],"an":[21],"assumption":[22,38,51,78],"about":[23],"the":[24,27,40,54,76,108,118,126,143],"isometry":[25,41],"of":[26,39,90,107,113],"two":[28,43],"spaces.":[29],"We":[30,62],"propose":[31,64],"a":[32,87,97],"technique":[33],"to":[34,131],"quantitatively":[35],"estimate":[36],"this":[37,50],"between":[42],"embedding":[44,127],"spaces":[45,128],"and":[46,86,121,146],"empirically":[47],"show":[48,138],"that":[49,74,139],"weakens":[52],"as":[53,94,96],"languages":[55],"in":[56],"question":[57],"become":[58],"increasingly":[59],"etymologically":[60],"distant.":[61],"then":[63],"Bilingual":[65],"Lexicon":[66],"Induction":[67],"Semi-Supervision":[69],"(BLISS)":[70],"-a":[71],"semi-supervised":[72],"approach":[73],"relaxes":[75],"isometric":[77],"while":[79],"leveraging":[80],"both":[81],"limited":[82],"larger":[88],"set":[89],"unaligned":[91],"word":[92],"embeddings,":[93],"well":[95,124],"novel":[98],"hubness":[99],"filtering":[100],"technique.":[101],"Our":[102],"proposed":[103],"method":[104],"obtains":[105],"state":[106],"art":[109],"results":[110],"15":[112],"18":[114],"language":[115],"pairs":[116],"MUSE":[119],"dataset,":[120],"does":[122],"particularly":[123],"when":[125],"don't":[129],"appear":[130],"be":[132],"isometric.":[133],"In":[134],"addition,":[135],"we":[136],"also":[137],"adding":[140],"supervision":[141],"stabilizes":[142],"learning":[144],"procedure,":[145],"is":[147],"effective":[148],"even":[149],"minimal":[151],"supervision.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":33},{"year":2020,"cited_by_count":23},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}
