{"id":"https://openalex.org/W4410949986","doi":"https://doi.org/10.1109/tnnls.2025.3569834","title":"CKDF-V2: Effectively Alleviating Representation Shift for Continual Learning With Small Memory","display_name":"CKDF-V2: Effectively Alleviating Representation Shift for Continual Learning With Small Memory","publication_year":2025,"publication_date":"2025-06-02","ids":{"openalex":"https://openalex.org/W4410949986","doi":"https://doi.org/10.1109/tnnls.2025.3569834","pmid":"https://pubmed.ncbi.nlm.nih.gov/40456090"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3569834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3569834","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5023566199","display_name":"Kunchi Li","orcid":"https://orcid.org/0000-0001-9874-3571"},"institutions":[{"id":"https://openalex.org/I75867142","display_name":"Xiamen University of Technology","ror":"https://ror.org/01285e189","country_code":"CN","type":"education","lineage":["https://openalex.org/I75867142"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kunchi Li","raw_affiliation_strings":["School of Computer and Information Engineering and Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology (XMUT), Xiamen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering and Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology (XMUT), Xiamen, China","institution_ids":["https://openalex.org/I75867142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008473103","display_name":"Hongyang Chen","orcid":"https://orcid.org/0000-0002-7626-0162"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyang Chen","raw_affiliation_strings":["Research Center for Graph Computing, Zhejiang Laboratory, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Graph Computing, Zhejiang Laboratory, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063979916","display_name":"Jun Wan","orcid":"https://orcid.org/0000-0002-4735-2885"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wan","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112762772","display_name":"Shan Yu","orcid":"https://orcid.org/0000-0002-4385-6306"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Yu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023566199"],"corresponding_institution_ids":["https://openalex.org/I75867142"],"apc_list":null,"apc_paid":null,"fwci":1.4909,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8221831,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"36","issue":"9","first_page":"16171","last_page":"16185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10918","display_name":"Memory Processes and Influences","score":0.7177000045776367,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10918","display_name":"Memory Processes and Influences","score":0.7177000045776367,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6480000019073486,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.6040999889373779,"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/representation","display_name":"Representation (politics)","score":0.5958967804908752},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.4461294412612915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4301331043243408},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3808612823486328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.364341676235199},{"id":"https://openalex.org/keywords/cognitive-science","display_name":"Cognitive science","score":0.353087455034256},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.16835403442382812}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5958967804908752},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.4461294412612915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4301331043243408},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3808612823486328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.364341676235199},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.353087455034256},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.16835403442382812},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3569834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3569834","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40456090","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40456090","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2180369873","display_name":null,"funder_award_id":"3502Z20241027","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G3485291661","display_name":null,"funder_award_id":"62476273","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4607961091","display_name":null,"funder_award_id":"62271452","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1682403713","https://openalex.org/W2108598243","https://openalex.org/W2895699061","https://openalex.org/W2954929116","https://openalex.org/W2962858109","https://openalex.org/W2963691377","https://openalex.org/W2964189064","https://openalex.org/W2982220706","https://openalex.org/W3015735225","https://openalex.org/W3034856281","https://openalex.org/W3034933032","https://openalex.org/W3096609285","https://openalex.org/W3097816393","https://openalex.org/W3107810305","https://openalex.org/W3108124733","https://openalex.org/W3163939464","https://openalex.org/W3177248386","https://openalex.org/W3180392831","https://openalex.org/W4210311961","https://openalex.org/W4214519401","https://openalex.org/W4214924370","https://openalex.org/W4225484930","https://openalex.org/W4286837396","https://openalex.org/W4307725500","https://openalex.org/W4312309344","https://openalex.org/W4312615142","https://openalex.org/W4382203080","https://openalex.org/W4385338523","https://openalex.org/W4386075492","https://openalex.org/W4386076680","https://openalex.org/W4390323078","https://openalex.org/W4392449669","https://openalex.org/W4392796474"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2931662336","https://openalex.org/W4220667126","https://openalex.org/W2077865380","https://openalex.org/W3006817050","https://openalex.org/W4401768695","https://openalex.org/W2765597752","https://openalex.org/W2134894512","https://openalex.org/W2083375246"],"abstract_inverted_index":{"In":[0,33],"continual":[1],"learning":[2],"(CL),":[3],"the":[4,12,22,26,55,58,68,85,89,93,99,106,115,119,126,129,135,153,174,192,216],"newly":[5],"arrived":[6],"data":[7,130,169],"are":[8,131],"often":[9],"out-of-distribution":[10],"from":[11],"previous":[13],"ones,":[14],"causing":[15],"drastic":[16],"representation":[17],"shift":[18],"(RS)":[19],"when":[20],"updating":[21],"old":[23,59,86,100,136],"model":[24],"on":[25,215],"new":[27,61,102,138],"data,":[28],"leading":[29],"to":[30,42,52,78,83,122,159,207],"catastrophic":[31],"forgetting.":[32],"this":[34,44,143],"work,":[35],"we":[36,145,177,199],"propose":[37,146,178],"feature":[38],"boosting":[39],"calibration":[40],"(FBC)":[41],"tackle":[43],"problem.":[45],"Specifically,":[46],"an":[47,72,188],"expanded":[48],"module":[49],"is":[50,76],"trained":[51,77],"learn":[53],"all":[54],"classes,":[56,62,103,128],"including":[57],"and":[60,101,137,162,230],"discovering":[63],"critical":[64],"features":[65,82,91],"missed":[66,81,90],"by":[67],"original/old":[69],"model.":[70],"Then,":[71],"FBC":[73],"network":[74,228],"(FBCN)":[75],"exploit":[79],"these":[80],"calibrate":[84],"representations.":[87],"As":[88],"increase":[92],"information":[94],"needed":[95],"for":[96,183,212],"distinguishing":[97],"between":[98,134],"FBCN":[104],"generates":[105],"calibrated":[107],"ones":[108],"with":[109,142,202],"more":[110],"transferable":[111],"features,":[112],"thus":[113],"alleviating":[114],"RS.":[116],"Next,":[117],"given":[118],"limited":[120],"memory":[121],"store":[123],"samples":[124],"of":[125,191],"old/learned":[127],"severely":[132],"imbalanced":[133],"classes.":[139],"To":[140],"cope":[141],"problem,":[144],"blockwise":[147],"knowledge":[148,194],"distillation":[149,195],"(BWKD),":[150],"which":[151],"splits":[152],"softmax":[154],"layer":[155],"into":[156],"blocks":[157],"according":[158],"class":[160],"frequency":[161],"then":[163],"distills":[164],"each":[165],"block":[166],"separately,":[167],"resolving":[168],"imbalance":[170],"effectively.":[171],"Building":[172],"upon":[173],"two":[175],"improvements,":[176],"a":[179,203,209,225],"two-stage":[180],"training":[181],"framework":[182,196],"CL,":[184],"named":[185],"CKDF-V2,":[186],"providing":[187],"enhanced":[189],"version":[190],"cascaded":[193],"(CKDF).":[197],"Furthermore,":[198],"integrate":[200],"it":[201],"task-token":[204],"expansion":[205],"method":[206],"develop":[208],"novel":[210],"approach":[211],"CL":[213,238],"based":[214],"vision":[217],"transformer":[218],"(ViT).":[219],"Extensive":[220],"experiments":[221],"show":[222],"that":[223],"both":[224],"convolutional":[226],"neural":[227],"(CNN)":[229],"ViT-based":[231],"CKDF-V2":[232],"obtain":[233],"favorable":[234],"results":[235],"across":[236],"multiple":[237],"benchmarks.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
