{"id":"https://openalex.org/W7166522512","doi":"https://doi.org/10.1145/3805689.3812330","title":"RobustDebias: Debiasing Language Models using Distributionally Robust Optimization","display_name":"RobustDebias: Debiasing Language Models using Distributionally Robust Optimization","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166522512","doi":"https://doi.org/10.1145/3805689.3812330"},"language":null,"primary_location":{"id":"doi:10.1145/3805689.3812330","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805689.3812330","pdf_url":null,"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 2026 ACM Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805689.3812330","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087294057","display_name":"Deep Gandhi","orcid":"https://orcid.org/0000-0001-7940-112X"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Deep Gandhi","raw_affiliation_strings":["University of Alberta, Edmonton, Canada, and Alberta Machine Intelligence Institute, Edmonton, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7940-112X","affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, Canada, and Alberta Machine Intelligence Institute, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036351750","display_name":"Katyani Singh","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Katyani Singh","raw_affiliation_strings":["University of Alberta, Edmonton, Canada, and Alberta Machine Intelligence Institute, Edmonton, Canada"],"raw_orcid":"https://orcid.org/0009-0005-2232-019X","affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, Canada, and Alberta Machine Intelligence Institute, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101806150","display_name":"Nidhi Hegde","orcid":"https://orcid.org/0000-0001-7385-3416"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Nidhi Hegde","raw_affiliation_strings":["University of Alberta, Edmonton, Canada, Alberta Machine Intelligence Institute, edmonton, Canada, and CIFAR AI Chair, Edmonton, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7385-3416","affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, Canada, Alberta Machine Intelligence Institute, edmonton, Canada, and CIFAR AI Chair, Edmonton, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154425047"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80803526,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3858","last_page":"3879"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.12520000338554382,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":0.12520000338554382,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.0957999974489212,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.06120000034570694,"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/debiasing","display_name":"Debiasing","score":0.7315000295639038},{"id":"https://openalex.org/keywords/robust-optimization","display_name":"Robust optimization","score":0.5536999702453613},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.38260000944137573},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.32030001282691956},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3199999928474426}],"concepts":[{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.7315000295639038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6140999794006348},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.5536999702453613},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.45879998803138733},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.38260000944137573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32829999923706055},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2888000011444092},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26829999685287476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805689.3812330","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805689.3812330","pdf_url":null,"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 2026 ACM Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805689.3812330","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805689.3812330","pdf_url":null,"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 2026 ACM Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3798759043","display_name":"Privacy in Machine Learning:  Scalability and Limits","funder_award_id":"dgecr-2021-00279","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1484551447","https://openalex.org/W2891177506","https://openalex.org/W2909212904","https://openalex.org/W2923014074","https://openalex.org/W2963078909","https://openalex.org/W2979826702","https://openalex.org/W3095992020","https://openalex.org/W3105882417","https://openalex.org/W3172415559","https://openalex.org/W3176477796","https://openalex.org/W3206487987","https://openalex.org/W4247118947","https://openalex.org/W4285192297","https://openalex.org/W4285258618","https://openalex.org/W4385570172","https://openalex.org/W4385574250","https://openalex.org/W4385893817","https://openalex.org/W4386246835"],"related_works":[],"abstract_inverted_index":{"University":[0],"of":[1],"Alberta,":[2],"Canada,":[3,8],"Alberta":[4],"Machine":[5],"Intelligence":[6],"Institute,":[7],"CIFAR":[9],"AI":[10],"Chair,":[11],"Canada":[12],"Pretrained":[13],"language":[14,86,121,146],"models":[15,30,49,79,122,128,147],"have":[16],"been":[17],"shown":[18],"to":[19,81,119,137],"exhibit":[20],"biases":[21,60,101],"and":[22,58,135],"social":[23,100],"stereotypes.":[24],"Prior":[25],"work":[26],"on":[27,34,50,77,144],"debiasing":[28],"these":[29],"has":[31],"largely":[32],"focused":[33],"modifying":[35],"embedding":[36],"spaces":[37],"during":[38,70,102,123,132],"pretraining,":[39,75],"which":[40,113],"is":[41],"not":[42],"scalable":[43],"for":[44],"large":[45],"models.":[46],"Fine-tuning":[47],"pretrained":[48],"task-specific":[51],"datasets":[52],"can":[53],"both":[54],"degrade":[55],"model":[56],"performance":[57,154],"amplify":[59],"present":[61],"in":[62,85],"the":[63],"fine-tuning":[64,71,134],"data.":[65],"We":[66],"address":[67],"bias":[68,150],"amplification":[69],"rather":[72],"than":[73],"costly":[74],"focusing":[76],"BERT":[78],"due":[80],"their":[82],"widespread":[83],"use":[84],"understanding":[87],"tasks.":[88],"While":[89],"Empirical":[90],"Risk":[91],"Minimization":[92],"effectively":[93],"optimizes":[94],"downstream":[95],"performance,":[96],"it":[97],"often":[98],"amplifies":[99],"fine-tuning.":[103,124],"To":[104],"counter":[105],"this,":[106],"we":[107],"propose":[108],"RobustDebias,":[109],"a":[110],"novel":[111],"mechanism":[112],"adapts":[114],"Distributionally":[115],"Robust":[116],"Optimization":[117],"(DRO)":[118],"debias":[120],"Our":[125],"approach":[126],"debiases":[127],"across":[129],"multiple":[130],"demographics":[131],"MLM":[133],"generalizes":[136],"any":[138],"dataset":[139],"or":[140],"task.":[141],"Extensive":[142],"experiments":[143],"various":[145],"show":[148],"significant":[149],"mitigation":[151],"with":[152],"minimal":[153],"impact.":[155]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-06-30T00:00:00"}