{"id":"https://openalex.org/W7139936124","doi":"https://doi.org/10.1016/j.procs.2026.01.019","title":"Federated Learning for Decentralized Language Model Training across Global Data Sources","display_name":"Federated Learning for Decentralized Language Model Training across Global Data Sources","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7139936124","doi":"https://doi.org/10.1016/j.procs.2026.01.019"},"language":"en","primary_location":{"id":"doi:10.1016/j.procs.2026.01.019","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2026.01.019","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.procs.2026.01.019","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130214449","display_name":"Nidhi Mishra","orcid":null},"institutions":[{"id":"https://openalex.org/I2800614057","display_name":"Kalinga University","ror":"https://ror.org/03afg5j45","country_code":"IN","type":"education","lineage":["https://openalex.org/I2800614057"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Nidhi Mishra","raw_affiliation_strings":["Kalinga University, Naya Raipur, Chhattisgarh, India"],"affiliations":[{"raw_affiliation_string":"Kalinga University, Naya Raipur, Chhattisgarh, India","institution_ids":["https://openalex.org/I2800614057"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005453284","display_name":"Parmanand Yadav","orcid":null},"institutions":[{"id":"https://openalex.org/I2800614057","display_name":"Kalinga University","ror":"https://ror.org/03afg5j45","country_code":"IN","type":"education","lineage":["https://openalex.org/I2800614057"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Parmanand Yadav","raw_affiliation_strings":["Kalinga University, Naya Raipur, Chhattisgarh, India"],"affiliations":[{"raw_affiliation_string":"Kalinga University, Naya Raipur, Chhattisgarh, India","institution_ids":["https://openalex.org/I2800614057"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5130214449"],"corresponding_institution_ids":["https://openalex.org/I2800614057"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93285128,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"275","issue":null,"first_page":"148","last_page":"156"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.24410000443458557,"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":0.24410000443458557,"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/T11719","display_name":"Data Quality and Management","score":0.1477999985218048,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14347","display_name":"Big Data and Digital Economy","score":0.08079999685287476,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/federated-learning","display_name":"Federated learning","score":0.7389000058174133},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.7016000151634216},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5174000263214111},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4803999960422516},{"id":"https://openalex.org/keywords/data-model","display_name":"Data model (GIS)","score":0.39410001039505005},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.37380000948905945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9225999712944031},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.7389000058174133},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.7016000151634216},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5174000263214111},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4803999960422516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.424699991941452},{"id":"https://openalex.org/C100463513","wikidata":"https://www.wikidata.org/wiki/Q5227322","display_name":"Data model (GIS)","level":2,"score":0.39410001039505005},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3061999976634979},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28619998693466187},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.27489998936653137},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2667999863624573},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.26100000739097595},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25870001316070557},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.25220000743865967}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.procs.2026.01.019","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2026.01.019","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.procs.2026.01.019","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2026.01.019","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.42612209916114807}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W4229004595","https://openalex.org/W4297478850","https://openalex.org/W4377293783","https://openalex.org/W4377428060","https://openalex.org/W4378976270","https://openalex.org/W4380080455","https://openalex.org/W4391260348","https://openalex.org/W4391476916","https://openalex.org/W4392113199","https://openalex.org/W4392284622","https://openalex.org/W4392357773","https://openalex.org/W4394753105","https://openalex.org/W4399468713","https://openalex.org/W4399811750","https://openalex.org/W4399874009","https://openalex.org/W4399881715","https://openalex.org/W4400210035","https://openalex.org/W4400526999","https://openalex.org/W4400850163","https://openalex.org/W4401114032","https://openalex.org/W4401580665","https://openalex.org/W4402102232","https://openalex.org/W4402331929","https://openalex.org/W4403107308","https://openalex.org/W4403987255","https://openalex.org/W4405142841","https://openalex.org/W4405493849","https://openalex.org/W4406857280","https://openalex.org/W4407382954","https://openalex.org/W4407466527","https://openalex.org/W4408128024","https://openalex.org/W4408254180","https://openalex.org/W4408743858","https://openalex.org/W4408781028","https://openalex.org/W4408788024","https://openalex.org/W4409687919","https://openalex.org/W4410529690","https://openalex.org/W4410639293","https://openalex.org/W4410992884","https://openalex.org/W4412044520","https://openalex.org/W4412123110"],"related_works":[],"abstract_inverted_index":{"Federated":[0,82],"learning":[1],"has":[2],"emerged":[3],"as":[4],"a":[5,81,110,165],"powerful":[6],"paradigm":[7],"for":[8,32,49,193],"training":[9,52],"language":[10,50,96,168,195],"models":[11,97],"across":[12,159,184],"decentralized":[13,194],"data":[14,36,42,57,138],"sources,":[15],"enabling":[16],"collaborative":[17],"model":[18,51,107,122,169,196],"development":[19],"without":[20,170],"the":[21,120],"need":[22],"to":[23,62,71,118,150,162],"centralize":[24],"sensitive":[25,127],"data.":[26,173],"This":[27,131],"approach":[28,132],"is":[29,129,148],"particularly":[30],"relevant":[31],"global-scale":[33],"applications":[34],"where":[35],"privacy,":[37],"legal":[38],"restrictions,":[39],"and":[40,68,102,140,157,186],"heterogeneous":[41,137],"distributions":[43],"pose":[44],"significant":[45],"challenges.":[46],"Existing":[47],"methods":[48],"often":[53],"rely":[54],"on":[55,98],"centralized":[56],"aggregation,":[58],"which":[59],"can":[60],"lead":[61],"privacy":[63,134,188],"breaches,":[64],"high":[65,180],"communication":[66,143],"costs,":[67],"limited":[69],"adaptability":[70],"diverse":[72],"local":[73,95],"datasets.":[74],"To":[75],"address":[76],"these":[77],"challenges,":[78],"we":[79],"propose":[80],"Averaging":[83],"with":[84,109],"Differential":[85],"Privacy":[86],"(FedAvg-DP)":[87],"framework.":[88],"In":[89],"this":[90],"framework,":[91],"individual":[92],"clients":[93],"train":[94],"their":[99],"private":[100,106],"datasets":[101],"share":[103],"only":[104],"differentially":[105],"updates":[108],"central":[111],"aggregator.":[112],"The":[113,145],"aggregator":[114],"performs":[115],"weighted":[116],"averaging":[117],"update":[119],"global":[121,166],"while":[123],"ensuring":[124],"that":[125,177],"no":[126],"information":[128],"exposed.":[130],"mitigates":[133],"risks,":[135],"accommodates":[136],"distributions,":[139],"reduces":[141],"network":[142],"overhead.":[144],"proposed":[146],"method":[147],"applied":[149],"cross-lingual":[151],"healthcare":[152],"chatbot":[153],"development,":[154],"allowing":[155],"hospitals":[156],"clinics":[158],"multiple":[160],"countries":[161],"collaboratively":[163],"improve":[164],"medical":[167],"sharing":[171],"patient":[172],"Experimental":[174],"results":[175],"demonstrate":[176],"FedAvg-DP":[178],"achieves":[179],"accuracy,":[181],"robust":[182],"generalization":[183],"languages,":[185],"strong":[187],"preservation,":[189],"confirming":[190],"its":[191],"effectiveness":[192],"training.":[197]},"counts_by_year":[],"updated_date":"2026-03-22T06:25:25.174409","created_date":"2026-03-21T00:00:00"}
