{"id":"https://openalex.org/W4412876923","doi":"https://doi.org/10.1145/3711896.3736902","title":"DarkDistill: Difficulty-Aligned Federated Early-Exit Network Training on Heterogeneous Devices","display_name":"DarkDistill: Difficulty-Aligned Federated Early-Exit Network Training on Heterogeneous Devices","publication_year":2025,"publication_date":"2025-08-03","ids":{"openalex":"https://openalex.org/W4412876923","doi":"https://doi.org/10.1145/3711896.3736902"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3736902","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736902","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736902","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736902","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119175114","display_name":"Lehao Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lehao Qu","raw_affiliation_strings":["SKLCCSE Lab, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-3373-5926","affiliations":[{"raw_affiliation_string":"SKLCCSE Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019901542","display_name":"Shuyuan Li","orcid":"https://orcid.org/0009-0008-1731-2541"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shuyuan Li","raw_affiliation_strings":["Department of Data Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0009-0008-1731-2541","affiliations":[{"raw_affiliation_string":"Department of Data Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011140675","display_name":"Zimu Zhou","orcid":"https://orcid.org/0000-0002-5457-6967"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zimu Zhou","raw_affiliation_strings":["Department of Data Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0002-5457-6967","affiliations":[{"raw_affiliation_string":"Department of Data Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039803393","display_name":"Boyi Liu","orcid":"https://orcid.org/0009-0004-5894-7878"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Boyi Liu","raw_affiliation_strings":["SKLCCSE Lab, Beihang University, City University of Hong Kong, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-5894-7878","affiliations":[{"raw_affiliation_string":"SKLCCSE Lab, Beihang University, City University of Hong Kong, Beijing, China","institution_ids":["https://openalex.org/I168719708","https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101403202","display_name":"Yi Xu","orcid":"https://orcid.org/0000-0002-2709-3652"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Xu","raw_affiliation_strings":["SKLCCSE Lab, Institute of Artificial Intelligence, Beihang University, beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2709-3652","affiliations":[{"raw_affiliation_string":"SKLCCSE Lab, Institute of Artificial Intelligence, Beihang University, beijing, China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051874566","display_name":"Yongxin Tong","orcid":"https://orcid.org/0000-0002-5598-0312"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxin Tong","raw_affiliation_strings":["SKLCCSE Lab, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5598-0312","affiliations":[{"raw_affiliation_string":"SKLCCSE Lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.8719,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.95200499,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2374","last_page":"2385"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9990000128746033,"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":0.9990000128746033,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9987999796867371,"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/T13553","display_name":"Age of Information Optimization","score":0.9962000250816345,"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/training","display_name":"Training (meteorology)","score":0.6871047019958496},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.670827329158783},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4131048619747162}],"concepts":[{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6871047019958496},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.670827329158783},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4131048619747162},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711896.3736902","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736902","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736902","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3711896.3736902","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736902","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736902","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2429891451","display_name":null,"funder_award_id":"62425202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3364513770","display_name":null,"funder_award_id":"2023YFF0725103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G351810823","display_name":null,"funder_award_id":"62336003","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G386271577","display_name":null,"funder_award_id":"2023YFF0725103","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4569554029","display_name":null,"funder_award_id":"9610633","funder_id":"https://openalex.org/F4320309893","funder_display_name":"City University of Hong Kong"},{"id":"https://openalex.org/G5762897086","display_name":null,"funder_award_id":"2023YFF0725103","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G6657135290","display_name":null,"funder_award_id":"JK2024-03","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8197150722","display_name":null,"funder_award_id":"U21A20516","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"},{"id":"https://openalex.org/F4320319065","display_name":"Aromatic Plant Research Center","ror":"https://ror.org/05eebgw43"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412876923.pdf","grobid_xml":"https://content.openalex.org/works/W4412876923.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W2210284195","https://openalex.org/W2251939518","https://openalex.org/W2430704425","https://openalex.org/W2473515811","https://openalex.org/W2541884796","https://openalex.org/W2610140147","https://openalex.org/W2613582265","https://openalex.org/W2800888853","https://openalex.org/W2902144984","https://openalex.org/W2945133121","https://openalex.org/W2962677625","https://openalex.org/W2963140444","https://openalex.org/W2968558963","https://openalex.org/W2981812042","https://openalex.org/W2987861506","https://openalex.org/W2997006708","https://openalex.org/W3116489684","https://openalex.org/W3165447760","https://openalex.org/W3168652588","https://openalex.org/W3169682907","https://openalex.org/W3170874841","https://openalex.org/W3174540410","https://openalex.org/W3205353516","https://openalex.org/W3212678506","https://openalex.org/W4221149037","https://openalex.org/W4226101686","https://openalex.org/W4290043197","https://openalex.org/W4290927763","https://openalex.org/W4296549614","https://openalex.org/W4312429345","https://openalex.org/W4313018220","https://openalex.org/W4318619660","https://openalex.org/W4382317673","https://openalex.org/W4382467688","https://openalex.org/W4386083155","https://openalex.org/W4388891035","https://openalex.org/W4396758732","https://openalex.org/W4404721440","https://openalex.org/W6600109629","https://openalex.org/W6720495657","https://openalex.org/W6761503440"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W230091440","https://openalex.org/W2390279801","https://openalex.org/W2233261550","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2810751659"],"abstract_inverted_index":{"Early-exit":[0],"networks":[1],"(EENs),":[2],"which":[3,30,54],"adapt":[4],"their":[5],"computational":[6],"depths":[7],"based":[8],"on":[9,27,77],"input":[10],"samples,":[11],"are":[12,74],"widely":[13],"adopted":[14],"to":[15],"accelerate":[16],"inference":[17],"in":[18,68,155],"edge":[19,59],"computing":[20],"applications.":[21],"The":[22],"effectiveness":[23],"of":[24,125,139,145,161],"EENs":[25,73,93],"relies":[26],"difficulty-aware":[28,45,66],"training,":[29],"tailors":[31],"shallow":[32],"exits":[33,39,144],"for":[34,40,119],"simple":[35],"samples":[36],"and":[37,134,158],"deep":[38],"complex":[41],"ones.":[42],"However,":[43],"existing":[44],"training":[46,67],"schemes":[47],"assume":[48],"centralized":[49],"environments":[50],"with":[51,57],"sufficient":[52],"data,":[53],"become":[55],"invalid":[56],"real-world":[58],"devices.":[60,79],"In":[61],"this":[62,101],"paper,":[63],"we":[64,103],"explore":[65],"a":[69,87,95,105],"federated":[70],"manner,":[71],"where":[72],"collaboratively":[75],"trained":[76],"heterogeneous":[78,121,146],"We":[80],"observe":[81],"the":[82,116,153],"cross-model":[83],"exit":[84],"unalignment":[85],"phenomenon,":[86],"unique":[88],"problem":[89],"when":[90],"aggregating":[91,120],"local":[92,122],"into":[94],"cohesive":[96],"global":[97],"model.":[98],"To":[99],"address":[100],"problem,":[102],"design":[104],"novel":[106],"Difficulty-Aligned":[107],"Reverse":[108],"Knowledge":[109],"Distillation":[110],"scheme":[111],"named":[112],"DarkDistill":[113,151],"that":[114,150],"preserves":[115],"difficulty-specific":[117],"specialization":[118],"models.":[123],"Instead":[124],"direct":[126],"parameter":[127],"averaging,":[128],"it":[129],"trains":[130],"difficulty-conditional":[131],"data":[132],"generators,":[133],"selectively":[135],"transfers":[136],"generated":[137],"knowledge":[138],"specific":[140],"difficulty":[141],"among":[142],"matched":[143],"EENs.":[147,162],"Evaluations":[148],"show":[149],"outperforms":[152],"state-of-the-arts":[154],"both":[156],"full-parameter":[157],"parameter-efficient":[159],"fine-tuning":[160]},"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-10-10T00:00:00"}