{"id":"https://openalex.org/W7084103428","doi":"https://doi.org/10.1109/infocom55648.2025.11044641","title":"Federated Adaptive Fine-Tuning of Large Language Models with Heterogeneous Quantization and LoRA","display_name":"Federated Adaptive Fine-Tuning of Large Language Models with Heterogeneous Quantization and LoRA","publication_year":2025,"publication_date":"2025-05-19","ids":{"openalex":"https://openalex.org/W7084103428","doi":"https://doi.org/10.1109/infocom55648.2025.11044641"},"language":"en","primary_location":{"id":"doi:10.1109/infocom55648.2025.11044641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom55648.2025.11044641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2025 - IEEE Conference on Computer Communications","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhidong Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhidong Gao","raw_affiliation_strings":["University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhenxiao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenxiao Zhang","raw_affiliation_strings":["University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuanxiong Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuanxiong Guo","raw_affiliation_strings":["University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yanmin Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanmin Gong","raw_affiliation_strings":["University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at San Antonio,Department of Electrical and Computer Engineering,San Antonio,USA","institution_ids":["https://openalex.org/I45438204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I45438204"],"apc_list":null,"apc_paid":null,"fwci":7.6539,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.97326416,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6610000133514404,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6610000133514404,"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/T13067","display_name":"Geological Modeling and Analysis","score":0.02419999986886978,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14311","display_name":"Electrical and Electromagnetic Research","score":0.020899999886751175,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.6186000108718872},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.595300018787384},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5697000026702881},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.52920001745224},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5174000263214111},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.39169999957084656},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.38960000872612},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3862000107765198}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8712999820709229},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.6186000108718872},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.595300018787384},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5697000026702881},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5461999773979187},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.52920001745224},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5174000263214111},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.39169999957084656},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3862000107765198},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.36809998750686646},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.35269999504089355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32280001044273376},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3147999942302704},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28110000491142273},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C3019252630","wikidata":"https://www.wikidata.org/wiki/Q6549547","display_name":"Limited resources","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.25040000677108765},{"id":"https://openalex.org/C3017813396","wikidata":"https://www.wikidata.org/wiki/Q17078173","display_name":"Resource constraints","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/infocom55648.2025.11044641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom55648.2025.11044641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2025 - IEEE Conference on Computer Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.41512638330459595}],"awards":[],"funders":[],"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],"with":[3,36],"parameter-efficient":[4],"fine-tuning":[5,18,35,64,96],"(PEFT)":[6],"methods,":[7],"such":[8],"as":[9],"Low-Rank":[10],"Adaptation":[11],"(LoRA),":[12],"offers":[13],"a":[14,57],"privacy-preserving":[15],"solution":[16],"for":[17,66],"large":[19],"language":[20],"models":[21],"(LLMs)":[22],"on":[23,97],"edge":[24],"devices.":[25],"However,":[26],"due":[27],"to":[28,81,122,138,178,185,188],"the":[29,83,91,140,144,156],"enormous":[30],"size":[31],"of":[32,158],"LLMs,":[33,67],"federated":[34,62],"LoRA":[37,87,92,117,134],"still":[38],"faces":[39],"significant":[40],"challenges,":[41,53],"including":[42],"high":[43],"training":[44,104,120,174],"latency":[45,105],"and":[46,60,73,88,99,106,126,130,163,180],"substantial":[47],"memory":[48,181],"requirements.":[49],"To":[50],"address":[51],"these":[52],"we":[54],"propose":[55],"FAH-QLoRA,":[56],"novel":[58],"time-":[59],"memory-efficient":[61],"adaptive":[63],"framework":[65],"which":[68],"leverages":[69],"heterogeneous":[70,100,133,149],"model":[71,85],"quantization":[72],"LoRA.":[74],"The":[75],"key":[76,112],"idea":[77],"behind":[78],"FAH-QLoRA":[79,109,159,171],"is":[80],"quantize":[82],"base":[84],"within":[86],"dynamically":[89,115],"adjust":[90],"ranks,":[93],"enabling":[94],"efficient":[95],"resource-constrained":[98],"devices":[101,137],"while":[102],"reducing":[103],"maintaining":[107],"performance.":[108],"integrates":[110],"two":[111],"techniques:":[113],"i)":[114],"adjusting":[116],"ranks":[118,135],"across":[119,136],"rounds":[121],"promote":[123],"faster":[124],"convergence":[125,157],"lower":[127],"resource":[128,150],"usage,":[129],"ii)":[131],"assigning":[132],"mitigate":[139],"straggler":[141],"effect":[142],"during":[143],"FL":[145,165],"process,":[146],"ensuring":[147],"that":[148,170],"constraints":[151],"are":[152],"met.":[153],"We":[154],"analyze":[155],"under":[160],"general":[161],"non-convex":[162],"non-IID":[164],"settings.":[166],"Extensive":[167],"experiments":[168],"demonstrate":[169],"can":[172],"reduce":[173],"time":[175],"by":[176,183],"up":[177,184],"45.86%":[179],"usage":[182],"44.15%":[186],"compared":[187],"baseline":[189],"methods.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
