{"id":"https://openalex.org/W7138345827","doi":"https://doi.org/10.1609/aaai.v40i29.39628","title":"CoRe-Fed: Bridging Collaborative and Representation Fairness via Federated Embedding Distillation","display_name":"CoRe-Fed: Bridging Collaborative and Representation Fairness via Federated Embedding Distillation","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138345827","doi":"https://doi.org/10.1609/aaai.v40i29.39628"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i29.39628","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39628","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39628/43589","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39628/43589","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Noorain Mukhtiar","orcid":null},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Noorain Mukhtiar","raw_affiliation_strings":["Macquarie University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Adnan Mahmood","orcid":null},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Adnan Mahmood","raw_affiliation_strings":["Macquarie University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":null,"display_name":"Quan Z. Sheng","orcid":null},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Quan Z. Sheng","raw_affiliation_strings":["Macquarie University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99043593"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20954357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"29","first_page":"24458","last_page":"24466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.737500011920929,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.737500011920929,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.09000000357627869,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.04960000142455101,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/bridging","display_name":"Bridging (networking)","score":0.7031999826431274},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6825000047683716},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5712000131607056},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5697000026702881},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5386000275611877},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48179998993873596},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4562000036239624},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4341999888420105}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8012999892234802},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.7031999826431274},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6825000047683716},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5712000131607056},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5697000026702881},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5386000275611877},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5023999810218811},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48179998993873596},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4562000036239624},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4341999888420105},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4325000047683716},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.41119998693466187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36329999566078186},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.352400004863739},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.33869999647140503},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.31929999589920044},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29330000281333923},{"id":"https://openalex.org/C2779582901","wikidata":"https://www.wikidata.org/wiki/Q21013010","display_name":"Distributed learning","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.2574999928474426},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i29.39628","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39628","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39628/43589","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/39628","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/39628","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i29.39628","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i29.39628","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39628/43589","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7410426139831543}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320591","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138345827.pdf","grobid_xml":"https://content.openalex.org/works/W7138345827.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"With":[0],"the":[1],"proliferation":[2],"of":[3,78],"distributed":[4],"data":[5,26,42],"sources,":[6],"Federated":[7],"Learning":[8],"(FL)":[9],"has":[10],"emerged":[11],"as":[12],"a":[13,92,125],"key":[14],"approach":[15],"to":[16,49,120,141],"enable":[17],"collaborative":[18,69,98],"intelligence":[19],"through":[20],"decentralized":[21],"model":[22,81,159],"training":[23],"while":[24],"preserving":[25],"privacy.":[27],"However,":[28],"conventional":[29],"FL":[30],"algorithms":[31],"often":[32],"suffer":[33],"from":[34,64,72],"performance":[35,82,160],"disparities":[36],"across":[37,147],"clients":[38],"caused":[39],"by":[40],"heterogeneous":[41],"distributions":[43],"and":[44,68,83,99,105,117,138,150,158],"unequal":[45],"participation,":[46],"which":[47,79],"leads":[48],"unfair":[50],"outcomes.":[51],"Specifically,":[52],"we":[53,89],"focus":[54],"on":[55,135],"two":[56],"core":[57],"fairness":[58,101,157],"challenges,":[59],"i.e.,":[60],"representation":[61,100],"bias,":[62,70],"arising":[63],"misaligned":[65],"client":[66],"representations,":[67],"stemming":[71],"inequitable":[73],"contribution":[74],"during":[75],"aggregation,":[76],"both":[77,156],"degrade":[80],"generalizability.":[84],"To":[85],"mitigate":[86],"these":[87],"disparities,":[88],"propose":[90],"CoRe-Fed,":[91],"unified":[93],"optimization":[94],"framework":[95],"that":[96,153],"bridges":[97],"via":[102],"embedding-level":[103],"regularization":[104],"fairness-aware":[106],"aggregation.":[107,144],"Initially,":[108],"an":[109],"alignment-driven":[110],"mechanism":[111],"promotes":[112],"semantic":[113],"consistency":[114],"between":[115],"local":[116],"global":[118],"embeddings":[119],"reduce":[121],"representational":[122],"divergence.":[123],"Subsequently,":[124],"dynamic":[126],"reward-penalty-based":[127],"aggregation":[128],"strategy":[129],"adjusts":[130],"each":[131],"client\u2019s":[132],"weight":[133],"based":[134],"participation":[136],"history":[137],"embedding":[139],"alignment":[140],"ensure":[142],"contribution-aware":[143],"Extensive":[145],"experiments":[146],"diverse":[148],"models":[149],"datasets":[151],"demonstrate":[152],"CoRe-Fed":[154],"improves":[155],"over":[161],"state-of-the-art":[162],"baseline":[163],"algorithms.":[164]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-06T00:00:00"}