{"id":"https://openalex.org/W4406840989","doi":"https://doi.org/10.1109/tc.2026.3655161","title":"Adaptive Rank Allocation for Federated Parameter-Efficient Fine-Tuning of Language Models","display_name":"Adaptive Rank Allocation for Federated Parameter-Efficient Fine-Tuning of Language Models","publication_year":2026,"publication_date":"2026-01-27","ids":{"openalex":"https://openalex.org/W4406840989","doi":"https://doi.org/10.1109/tc.2026.3655161"},"language":"en","primary_location":{"id":"doi:10.1109/tc.2026.3655161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2026.3655161","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","0016-9340","1557-9956","2326-3814"],"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 Transactions on Computers","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/2501.14406","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Fei Wu","orcid":"https://orcid.org/0000-0001-5149-1143"},"institutions":[{"id":"https://openalex.org/I23923803","display_name":"University of Exeter","ror":"https://ror.org/03yghzc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I23923803"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Fei Wu","raw_affiliation_strings":["Department of Computer Science, University of Exeter, Exeter, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5149-1143","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Exeter, Exeter, U.K","institution_ids":["https://openalex.org/I23923803"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jia Hu","orcid":"https://orcid.org/0000-0001-5406-8420"},"institutions":[{"id":"https://openalex.org/I23923803","display_name":"University of Exeter","ror":"https://ror.org/03yghzc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I23923803"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jia Hu","raw_affiliation_strings":["Department of Computer Science, University of Exeter, Exeter, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5406-8420","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Exeter, Exeter, U.K","institution_ids":["https://openalex.org/I23923803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116039182","display_name":"Geyong Min","orcid":null},"institutions":[{"id":"https://openalex.org/I23923803","display_name":"University of Exeter","ror":"https://ror.org/03yghzc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I23923803"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Geyong Min","raw_affiliation_strings":["Department of Computer Science, University of Exeter, Exeter, U.K"],"raw_orcid":"https://orcid.org/0000-0003-1395-7314","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Exeter, Exeter, U.K","institution_ids":["https://openalex.org/I23923803"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081221094","display_name":"S.P Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I23923803","display_name":"University of Exeter","ror":"https://ror.org/03yghzc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I23923803"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shiqiang Wang","raw_affiliation_strings":["Department of Computer Science, University of Exeter, Exeter, U.K"],"raw_orcid":"https://orcid.org/0000-0003-2090-5512","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Exeter, Exeter, U.K","institution_ids":["https://openalex.org/I23923803"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I23923803"],"apc_list":null,"apc_paid":null,"fwci":19.1295,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.98214715,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"75","issue":"4","first_page":"1650","last_page":"1663"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.91839998960495,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.91839998960495,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9121000170707703,"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/T10028","display_name":"Topic Modeling","score":0.9114000201225281,"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/rank","display_name":"Rank (graph theory)","score":0.7735925912857056},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5963867902755737},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1956002116203308},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0988430380821228}],"concepts":[{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.7735925912857056},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5963867902755737},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1956002116203308},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0988430380821228}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tc.2026.3655161","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tc.2026.3655161","pdf_url":null,"source":{"id":"https://openalex.org/S157670870","display_name":"IEEE Transactions on Computers","issn_l":"0018-9340","issn":["0018-9340","0016-9340","1557-9956","2326-3814"],"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 Transactions on Computers","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2501.14406","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.14406","pdf_url":"https://arxiv.org/pdf/2501.14406","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":"pmh:doi:10.48550/arxiv.2501.14406","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2501.14406","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2501.14406","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:2501.14406","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.14406","pdf_url":"https://arxiv.org/pdf/2501.14406","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/G1105131427","display_name":null,"funder_award_id":"101129910","funder_id":"https://openalex.org/F4320334322","funder_display_name":"HORIZON EUROPE Framework Programme"},{"id":"https://openalex.org/G7032785482","display_name":"Real-Time Federated Learning at the Wireless Edge via Algorithm-Hardware Co-Design","funder_award_id":"EP/X019160/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334322","display_name":"HORIZON EUROPE Framework Programme","ror":null},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406840989.pdf","grobid_xml":"https://content.openalex.org/works/W4406840989.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Pre-trained":[0],"Language":[1,13],"Models":[2],"(PLMs)":[3],"have":[4],"demonstrated":[5],"their":[6],"superiority":[7],"and":[8,38,69,153,179,204,211],"versatility":[9],"in":[10,41,75,156,200],"modern":[11],"Natural":[12],"Processing":[14],"(NLP),":[15],"effectively":[16,133],"adapting":[17],"to":[18,35,107,128,143,174,209],"various":[19,177,194],"downstream":[20],"tasks":[21],"through":[22],"further":[23],"fine-tuning.":[24],"Federated":[25],"Parameter-Efficient":[26],"Fine-Tuning":[27],"(FedPEFT)":[28],"has":[29],"emerged":[30],"as":[31],"a":[32,70,85],"promising":[33],"solution":[34],"address":[36],"privacy":[37],"efficiency":[39,188],"challenges":[40],"distributed":[42],"training":[43,202],"for":[44,91],"PLMs":[45],"on":[46,193],"resource-constrained":[47],"local":[48,150],"devices.":[49],"However,":[50],"our":[51],"measurements":[52],"reveal":[53],"two":[54],"key":[55],"limitations":[56],"of":[57,66,95,119,172],"FedPEFT:":[58],"heterogeneous":[59,182],"data":[60,120,183],"across":[61,112,176],"devices":[62,196],"exacerbates":[63],"performance":[64],"degradation":[65],"low-rank":[67],"adaptation,":[68],"fixed":[71],"parameter":[72],"configuration":[73],"results":[74],"communication":[76,135,187],"inefficiency.":[77],"To":[78],"overcome":[79],"these":[80],"limitations,":[81],"we":[82],"propose":[83],"FedARA,":[84],"novel":[86],"Adaptive":[87],"Rank":[88],"Allocation":[89],"framework":[90],"federated":[92,158],"parameter-efficient":[93],"fine-tuning":[94],"language":[96],"models.":[97],"Specifically,":[98],"FedARA":[99,165],"employs":[100],"truncated":[101],"Singular":[102],"Value":[103],"Decomposition":[104],"(SVD)":[105],"adaptation":[106],"enhance":[108],"similar":[109],"feature":[110],"representation":[111],"clients,":[113],"significantly":[114,185],"mitigating":[115],"the":[116],"adverse":[117],"effects":[118],"heterogeneity.":[121],"Subsequently,":[122],"it":[123,138],"utilizes":[124],"dynamic":[125],"rank":[126],"allocation":[127],"progressively":[129],"identify":[130],"critical":[131],"ranks,":[132],"improving":[134,186],"efficiency.":[136],"Lastly,":[137],"leverages":[139],"rank-based":[140],"module":[141],"pruning":[142],"automatically":[144],"remove":[145],"inactive":[146],"modules,":[147],"steadily":[148],"reducing":[149],"computational":[151],"cost":[152],"memory":[154],"usage":[155],"each":[157],"learning":[159],"round.":[160],"Extensive":[161],"experiments":[162,192],"show":[163],"that":[164],"consistently":[166],"outperforms":[167],"baselines":[168],"by":[169,189,207],"an":[170],"average":[171],"6.95%":[173],"8.49%":[175],"datasets":[178],"models":[180],"under":[181],"while":[184],"2.40\u00d7.":[190],"Moreover,":[191],"edge":[195],"demonstrate":[197],"substantial":[198],"decreases":[199],"total":[201],"time":[203],"energy":[205],"consumption":[206],"up":[208],"48.90%":[210],"46.95%,":[212],"respectively.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-26T07:53:14.480251","created_date":"2025-01-28T00:00:00"}