{"id":"https://openalex.org/W4402897338","doi":"https://doi.org/10.1109/iwqos61813.2024.10682866","title":"CP<sup>2</sup>GFed: Cross-granular and Personalized Prompt-based Green Federated Tuning for Giant Models","display_name":"CP<sup>2</sup>GFed: Cross-granular and Personalized Prompt-based Green Federated Tuning for Giant Models","publication_year":2024,"publication_date":"2024-06-19","ids":{"openalex":"https://openalex.org/W4402897338","doi":"https://doi.org/10.1109/iwqos61813.2024.10682866"},"language":"en","primary_location":{"id":"doi:10.1109/iwqos61813.2024.10682866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwqos61813.2024.10682866","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS)","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5006918284","display_name":"Fei Gao","orcid":"https://orcid.org/0000-0001-9076-9718"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Gao","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067139701","display_name":"Yunfeng Zhao","orcid":"https://orcid.org/0000-0002-1442-992X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfeng Zhao","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007510770","display_name":"Chao Qiu","orcid":"https://orcid.org/0000-0002-2224-2292"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Qiu","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100363467","display_name":"Xiao\u2010Fei Wang","orcid":"https://orcid.org/0000-0002-4659-9931"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Wang","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108154638","display_name":"Haipeng Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haipeng Yao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Information and Communication Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Information and Communication Engineering,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101786145","display_name":"Qinghua Hu","orcid":"https://orcid.org/0009-0009-6885-9480"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Hu","raw_affiliation_strings":["Tianjin University,College of Intelligence and Computing,Tianjin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University,College of Intelligence and Computing,Tianjin,China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2629,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.54660015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.97079998254776,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.97079998254776,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9379000067710876,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.9308000206947327,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5354549884796143}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5354549884796143}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwqos61813.2024.10682866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwqos61813.2024.10682866","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1567512734","https://openalex.org/W1680189815","https://openalex.org/W2069590084","https://openalex.org/W2081580037","https://openalex.org/W2807006176","https://openalex.org/W2896404430","https://openalex.org/W2990789643","https://openalex.org/W3037047862","https://openalex.org/W3038022836","https://openalex.org/W3109847748","https://openalex.org/W3112044954","https://openalex.org/W3113024443","https://openalex.org/W3133814152","https://openalex.org/W3156310591","https://openalex.org/W3195577433","https://openalex.org/W3198377975","https://openalex.org/W3205564238","https://openalex.org/W4283215940","https://openalex.org/W4285247752","https://openalex.org/W4287332481","https://openalex.org/W4309208182","https://openalex.org/W4312306383","https://openalex.org/W4312651322","https://openalex.org/W4312785780","https://openalex.org/W4312980231","https://openalex.org/W4367046615","https://openalex.org/W4385627126","https://openalex.org/W4386076590","https://openalex.org/W4389076571","https://openalex.org/W6728757088","https://openalex.org/W6752029299","https://openalex.org/W6759238902","https://openalex.org/W6770590064","https://openalex.org/W6782317661","https://openalex.org/W6790019176","https://openalex.org/W6791353385","https://openalex.org/W6800751262","https://openalex.org/W6802464851","https://openalex.org/W6802517928","https://openalex.org/W6803156713","https://openalex.org/W6846725466","https://openalex.org/W6850000361"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Giant":[0],"models":[1,21],"have":[2],"transformed":[3],"vision-language":[4],"tasks":[5],"by":[6,39,105,156,172,183],"mastering":[7],"consistent":[8],"representations":[9],"across":[10,123],"text":[11],"and":[12,32,45,62,83,92,154,161,179,197],"images,":[13],"highlighting":[14],"the":[15,23,35],"critical":[16],"role":[17],"of":[18,26,188],"deploying":[19],"such":[20,29],"in":[22,130],"expanding":[24],"domain":[25],"edge":[27],"scenarios,":[28],"as":[30,53],"monitoring":[31],"segmentation.":[33],"However,":[34],"deployment":[36,109],"is":[37],"challenged":[38],"device":[40],"heterogeneity,":[41],"limited":[42],"computational":[43],"resources,":[44],"privacy":[46],"concerns.":[47],"Federated":[48],"learning":[49,153],"(FL)":[50],"presents":[51],"itself":[52],"a":[54,90,114,191],"viable":[55],"solution,":[56],"facilitating":[57],"decentralized":[58],"training":[59],"on":[60,110,136,176],"devices":[61],"preserving":[63],"data":[64,125],"confidentiality.":[65],"Despite":[66],"its":[67],"potential,":[68],"FL":[69],"faces":[70],"obstacles":[71],"with":[72],"fine-tuning":[73],"efficiency,":[74],"including":[75,150],"complex":[76],"granularity":[77],"data,":[78],"static":[79],"personalized":[80,93,133],"prompt":[81],"generation,":[82],"high":[84],"energy":[85,148,181,198],"consumption.":[86],"This":[87],"paper":[88],"introduces":[89,113],"cross-granular":[91],"prompt-based":[94],"green":[95],"federated":[96],"tuning":[97],"(CP2GFed)":[98],"approach,":[99],"aiming":[100],"to":[101,119,139,174,201],"address":[102],"these":[103],"issues":[104],"enabling":[106],"giant":[107],"model":[108,141,151,195],"devices.":[111,164],"CP2GFed":[112,145,169],"cross-granularity":[115],"knowledge":[116],"transfer":[117],"mechanism":[118],"leverage":[120],"semantic":[121],"relationships":[122],"varying":[124],"granularities.":[126],"Meanwhile,":[127],"it":[128],"pioneers":[129],"generating":[131],"dynamic":[132],"prompts":[134],"based":[135],"inter-device":[137],"affinities":[138],"improve":[140],"performance.":[142],"In":[143],"addition,":[144],"meticulously":[146],"optimizes":[147],"consumption,":[149],"local":[152,158],"interaction,":[155],"setting":[157],"computing":[159],"steps":[160],"selecting":[162],"communication":[163],"Empirical":[165],"results":[166],"indicate":[167],"that":[168],"elevates":[170],"accuracy":[171],"up":[173],"6.64%":[175],"diverse":[177],"datasets":[178],"reduces":[180],"consumption":[182,199],"nearly":[184],"60%":[185],"per":[186],"unit":[187],"accuracy,":[189],"achieving":[190],"superior":[192],"tradeoff":[193],"between":[194],"performance":[196],"compared":[200],"baselines.":[202]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
