{"id":"https://openalex.org/W4415917252","doi":"https://doi.org/10.1109/jiot.2026.3652363","title":"FedSM: Semantic-Guided Feature Mixup for Bias Reduction in Federated Learning With Long-Tail Data","display_name":"FedSM: Semantic-Guided Feature Mixup for Bias Reduction in Federated Learning With Long-Tail Data","publication_year":2026,"publication_date":"2026-01-12","ids":{"openalex":"https://openalex.org/W4415917252","doi":"https://doi.org/10.1109/jiot.2026.3652363"},"language":null,"primary_location":{"id":"doi:10.1109/jiot.2026.3652363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3652363","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.27240","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jingrui Zhang","orcid":"https://orcid.org/0009-0006-0067-0532"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingrui Zhang","raw_affiliation_strings":["Guangdong–Hong Kong–Macau Joint Laboratory for Emotional Intelligence and Pervasive Computing, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0006-0067-0532","affiliations":[{"raw_affiliation_string":"Guangdong–Hong Kong–Macau Joint Laboratory for Emotional Intelligence and Pervasive Computing, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yimeng Xu","orcid":"https://orcid.org/0009-0005-3848-4308"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yimeng Xu","raw_affiliation_strings":["Guangdong–Hong Kong–Macau Joint Laboratory for Emotional Intelligence and Pervasive Computing, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0005-3848-4308","affiliations":[{"raw_affiliation_string":"Guangdong–Hong Kong–Macau Joint Laboratory for Emotional Intelligence and Pervasive Computing, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100728142","display_name":"Shujie Li","orcid":"https://orcid.org/0000-0001-5239-2454"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shujie Li","raw_affiliation_strings":["Department of Electrical and Electronic Engineering (HKU EEE), The University of Hong Kong, Pokfulam, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-5239-2454","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering (HKU EEE), The University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101890277","display_name":"Feng Liang","orcid":"https://orcid.org/0000-0002-8542-9871"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Liang","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8542-9871","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068512767","display_name":"Haihan Duan","orcid":"https://orcid.org/0000-0001-6438-3790"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haihan Duan","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6438-3790","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yanjie Dong","orcid":"https://orcid.org/0000-0002-5623-0249"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjie Dong","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-5623-0249","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035919267","display_name":"Victor C. M. Leung","orcid":"https://orcid.org/0000-0003-3529-2640"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Victor C. M. Leung","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-3529-2640","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007941489","display_name":"Xiping Hu","orcid":"https://orcid.org/0000-0002-4952-699X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiping Hu","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-4952-699X","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":20.0658,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.98331568,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"13","issue":"6","first_page":"12491","last_page":"12500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.7986000180244446,"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":0.7986000180244446,"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.015399999916553497,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.014700000174343586,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7342000007629395},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.7168999910354614},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6115999817848206},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5827999711036682},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.5095000267028809},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.40450000762939453},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4000000059604645},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.3634999990463257}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9014000296592712},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7342000007629395},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7168999910354614},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6115999817848206},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5827999711036682},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5583999752998352},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.5095000267028809},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.40450000762939453},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3646000027656555},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.3564000129699707},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3467000126838684},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32659998536109924},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.25519999861717224}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jiot.2026.3652363","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2026.3652363","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Internet of Things Journal","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2510.27240","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.27240","pdf_url":"https://arxiv.org/pdf/2510.27240","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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.2510.27240","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.27240","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.27240","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.27240","pdf_url":"https://arxiv.org/pdf/2510.27240","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6245907696","display_name":null,"funder_award_id":"2024KCXTD017","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G8465124245","display_name":null,"funder_award_id":"62576213","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0],"Learning":[1],"(FL)":[2],"has":[3],"emerged":[4],"as":[5],"a":[6,14,23,43,63],"promising":[7],"paradigm":[8],"for":[9,171],"decentralized":[10],"machine":[11],"learning,":[12],"where":[13],"central":[15],"server":[16,141],"coordinates":[17],"distributed":[18],"clients":[19,41],"to":[20,29,75,96],"collaboratively":[21],"train":[22],"global":[24,77,113],"model":[25,78],"without":[26],"direct":[27],"access":[28],"raw":[30],"data.":[31],"Despite":[32],"its":[33,169],"advantages,":[34],"heterogeneous":[35],"and":[36,53,93,121,143,158],"long-tail":[37,153],"data":[38,99],"distributions":[39],"across":[40],"remain":[42],"major":[44],"bottleneck,":[45],"particularly":[46],"in":[47,146,175],"IoT":[48,148,176],"scenarios":[49],"with":[50,71,112],"diverse":[51],"devices":[52],"sensing":[54],"modalities.":[55],"To":[56],"address":[57],"these":[58],"challenges,":[59],"we":[60],"propose":[61],"FedSM,":[62],"novel":[64],"framework":[65],"that":[66,83],"integrates":[67],"multimodal":[68],"semantic":[69],"knowledge":[70],"balanced":[72],"pseudo":[73,116],"features":[74,108,117],"enhance":[76],"optimization.":[79],"Unlike":[80],"conventional":[81],"approaches":[82],"rely":[84],"on":[85,152],"single-modal":[86],"information,":[87],"FedSM":[88,164],"leverages":[89],"CLIP\u2019s":[90],"cross-modal":[91],"representations":[92],"open-vocabulary":[94],"priors":[95],"guide":[97],"semantic-aware":[98],"augmentation.":[100],"A":[101],"probabilistic":[102],"selection":[103],"mechanism":[104],"further":[105],"refines":[106],"local":[107],"by":[109,125],"mixing":[110],"them":[111],"prototypes,":[114],"ensuring":[115],"are":[118,132],"semantically":[119],"reliable":[120],"reducing":[122],"bias":[123],"caused":[124],"skewed":[126],"client":[127,137],"distributions.":[128],"Almost":[129],"all":[130],"computations":[131],"performed":[133],"locally":[134],"at":[135],"the":[136,161],"side,":[138],"thereby":[139],"alleviating":[140],"overhead":[142],"improving":[144],"scalability":[145],"resource-constrained":[147],"environments.":[149],"Extensive":[150],"experiments":[151],"benchmarks":[154],"including":[155],"CIFAR-10-LT,":[156],"CIFAR-100-LT,":[157],"ImageNet-LT":[159],"demonstrate":[160],"superiority":[162],"of":[163],"over":[165],"state-of-the-art":[166],"baselines,":[167],"highlighting":[168],"potential":[170],"robust":[172],"communication-efficient":[173],"FL":[174],"networks.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-20T07:56:41.581041","created_date":"2025-11-05T00:00:00"}