{"id":"https://openalex.org/W2963524349","doi":"https://doi.org/10.18653/v1/p19-2031","title":"Reducing Gender Bias in Word-Level Language Models with a Gender-Equalizing Loss Function","display_name":"Reducing Gender Bias in Word-Level Language Models with a Gender-Equalizing Loss Function","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2963524349","doi":"https://doi.org/10.18653/v1/p19-2031","mag":"2963524349"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-2031","doi":"https://doi.org/10.18653/v1/p19-2031","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-2031","pdf_url":"https://www.aclweb.org/anthology/P19-2031.pdf","source":{"id":"https://openalex.org/S7407088936","display_name":"Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL SRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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: Student Research Workshop","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.aclweb.org/anthology/P19-2031.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090922071","display_name":"Yusu Qian","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yusu Qian","raw_affiliation_strings":["School of Engineering New York University 6","MetroTech Center Brooklyn, NY, 11201","Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","Department of Computer Science New York University 251 Mercer St New York, NY, 10012","School of Engineering New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering New York University 6","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"MetroTech Center Brooklyn, NY, 11201","institution_ids":[]},{"raw_affiliation_string":"Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Department of Computer Science New York University 251 Mercer St New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"School of Engineering New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004394596","display_name":"Urwa Muaz","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Urwa Muaz","raw_affiliation_strings":["Tandon School of Engineering New York University 6 MetroTech Center Brooklyn , NY , 11201","MetroTech Center Brooklyn, NY, 11201","Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","Department of Computer Science New York University 251 Mercer St New York, NY, 10012","School of Engineering New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tandon School of Engineering New York University 6 MetroTech Center Brooklyn , NY , 11201","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"MetroTech Center Brooklyn, NY, 11201","institution_ids":[]},{"raw_affiliation_string":"Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Department of Computer Science New York University 251 Mercer St New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"School of Engineering New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100700612","display_name":"Ben Zhang","orcid":"https://orcid.org/0000-0002-8957-4638","observed_orcids":["https://orcid.org/0000-0002-8957-4638"]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ben Zhang","raw_affiliation_strings":["Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","MetroTech Center Brooklyn, NY, 11201","Department of Computer Science New York University 251 Mercer St New York, NY, 10012","School of Engineering New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"MetroTech Center Brooklyn, NY, 11201","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science New York University 251 Mercer St New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"School of Engineering New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010090397","display_name":"Jae Won Hyun","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jae Won Hyun","raw_affiliation_strings":["MetroTech Center Brooklyn, NY, 11201","Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","Department of Computer Science New York University 251 Mercer St New York, NY, 10012","School of Engineering New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MetroTech Center Brooklyn, NY, 11201","institution_ids":[]},{"raw_affiliation_string":"Center for Data Science New York University 60 Fifth Avenue New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"Department of Computer Science New York University 251 Mercer St New York, NY, 10012","institution_ids":["https://openalex.org/I57206974"]},{"raw_affiliation_string":"School of Engineering New York University","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":9.6331,"has_fulltext":true,"cited_by_count":63,"citation_normalized_percentile":{"value":0.97587049,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"223","last_page":"228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.7699999809265137,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.7699999809265137,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13173","display_name":"Gender Studies in Language","score":0.06260000169277191,"subfield":{"id":"https://openalex.org/subfields/3318","display_name":"Gender Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.05209999904036522,"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/gender-bias","display_name":"gender bias","score":0.9869999885559082},{"id":"https://openalex.org/keywords/bias-mitigation","display_name":"bias mitigation","score":0.7730000019073486},{"id":"https://openalex.org/keywords/loss-function-modification","display_name":"loss function modification","score":0.8870000243186951},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.6809999942779541},{"id":"https://openalex.org/keywords/word-embeddings","display_name":"word embeddings","score":0.5649999976158142},{"id":"https://openalex.org/keywords/text-generation","display_name":"text generation","score":0.593999981880188}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.9885027408599854},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.8924466371536255},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7611904144287109},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5890509486198425},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5679176449775696},{"id":"https://openalex.org/C2983427547","wikidata":"https://www.wikidata.org/wiki/Q93200","display_name":"Gender bias","level":2,"score":0.5545620918273926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5344471335411072},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.47477030754089355},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46513810753822327},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3948691487312317},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.18879982829093933},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.11229285597801208},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.09085160493850708},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/p19-2031","doi":"https://doi.org/10.18653/v1/p19-2031","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-2031","pdf_url":"https://www.aclweb.org/anthology/P19-2031.pdf","source":{"id":"https://openalex.org/S7407088936","display_name":"Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL SRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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: Student Research Workshop","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1905.12801","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.12801","pdf_url":"https://arxiv.org/pdf/1905.12801","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1905.12801","doi":"https://doi.org/10.48550/arxiv.1905.12801","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1905.12801","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-2031","doi":"https://doi.org/10.18653/v1/p19-2031","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-2031","pdf_url":"https://www.aclweb.org/anthology/P19-2031.pdf","source":{"id":"https://openalex.org/S7407088936","display_name":"Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (ACL SRW)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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: Student Research Workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7578999996185303},{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.6025999784469604}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963524349.pdf","grobid_xml":"https://content.openalex.org/works/W2963524349.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W196214544","https://openalex.org/W1544827683","https://openalex.org/W2250539671","https://openalex.org/W2483215953","https://openalex.org/W2889624842","https://openalex.org/W2921633540","https://openalex.org/W2942370121","https://openalex.org/W2950018712","https://openalex.org/W2962787423","https://openalex.org/W3037697022","https://openalex.org/W3122810052","https://openalex.org/W3128232076"],"related_works":["https://openalex.org/W2942370121","https://openalex.org/W3128232076","https://openalex.org/W4372266800","https://openalex.org/W3159471930","https://openalex.org/W2888167352","https://openalex.org/W4287889476","https://openalex.org/W4399111298","https://openalex.org/W4402683076","https://openalex.org/W4309135082","https://openalex.org/W7160274807"],"abstract_inverted_index":{"Gender":[0],"bias":[1,57,70,101,124],"exists":[2],"in":[3,15,51,71,94,98,102,122],"natural":[4],"language":[5,9,72],"datasets":[6],"which":[7,40],"neural":[8],"models":[10,73],"tend":[11],"to":[12,36,42,80],"learn,":[13],"resulting":[14],"biased":[16],"text":[17],"generation.In":[18],"this":[19],"research,":[20],"we":[21,60,105],"propose":[22],"a":[23,33,107],"debiasing":[24,82],"approach":[25,66],"based":[26],"on":[27],"the":[28,37,44,52],"loss":[29,38],"function":[30,39],"modification.We":[31],"introduce":[32,106],"new":[34],"term":[35],"attempts":[41],"equalize":[43],"probabilities":[45],"of":[46,56,109],"male":[47],"and":[48,86,112,115],"female":[49],"words":[50],"output.Using":[53],"an":[54],"array":[55],"evaluation":[58,125],"metrics,":[59],"provide":[61],"empirical":[62],"evidence":[63],"that":[64,117],"our":[65,90,113],"successfully":[67],"mitigates":[68],"gender":[69,100],"without":[74],"increasing":[75],"perplexity":[76],"by":[77],"much.In":[78],"comparison":[79],"existing":[81,120],"strategies,":[83],"data":[84,110],"augmentation,":[85],"word":[87],"embedding":[88],"debiasing,":[89],"method":[91],"performs":[92],"better":[93],"several":[95],"aspects,":[96],"especially":[97],"reducing":[99],"occupation":[103],"words.Finally,":[104],"combination":[108],"augmentation":[111],"approach,":[114],"show":[116],"it":[118],"outperforms":[119],"strategies":[121],"all":[123],"metrics.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":2}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2019-07-30T00:00:00"}