{"id":"https://openalex.org/W4414566547","doi":"https://doi.org/10.1109/iccv51701.2025.00039","title":"Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental Learning","display_name":"Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental Learning","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4414566547","doi":"https://doi.org/10.1109/iccv51701.2025.00039"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.00039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.07979","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100353673","display_name":"Hao Chen","orcid":"https://orcid.org/0009-0001-6480-7976"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Chen","raw_affiliation_strings":["Institute of Trustworthy Embodied AI, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Trustworthy Embodied AI, Fudan University","institution_ids":["https://openalex.org/I4210139618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338632","display_name":"Ping Wang","orcid":"https://orcid.org/0000-0002-1557-0394"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Wang","raw_affiliation_strings":["Institute of Trustworthy Embodied AI, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Trustworthy Embodied AI, Fudan University","institution_ids":["https://openalex.org/I4210139618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113221770","display_name":"Zihan Zhou","orcid":"https://orcid.org/0009-0003-0155-550X"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zihan Zhou","raw_affiliation_strings":["Institute of Trustworthy Embodied AI, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Trustworthy Embodied AI, Fudan University","institution_ids":["https://openalex.org/I4210139618"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437262","display_name":"Xu Zhang","orcid":"https://orcid.org/0000-0002-8098-8893"},"institutions":[{"id":"https://openalex.org/I23821868","display_name":"American Public University System","ror":"https://ror.org/02890tv09","country_code":"US","type":"education","lineage":["https://openalex.org/I23821868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xu Zhang","raw_affiliation_strings":["APUS AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"APUS AI Lab","institution_ids":["https://openalex.org/I23821868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026167547","display_name":"Zuxuan Wu","orcid":"https://orcid.org/0000-0002-8689-5807"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuxuan Wu","raw_affiliation_strings":["Institute of Trustworthy Embodied AI, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Trustworthy Embodied AI, Fudan University","institution_ids":["https://openalex.org/I4210139618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047962986","display_name":"Yu\u2013Gang Jiang","orcid":"https://orcid.org/0000-0002-1907-8567"},"institutions":[{"id":"https://openalex.org/I4210139618","display_name":"Shanghai Key Laboratory of Trustworthy Computing","ror":"https://ror.org/030qbr085","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210139618"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu-Gang Jiang","raw_affiliation_strings":["Institute of Trustworthy Embodied AI, Fudan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Trustworthy Embodied AI, Fudan University","institution_ids":["https://openalex.org/I4210139618"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"340","last_page":"349"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11122","display_name":"Online Learning and Analytics","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9344000220298767,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9179999828338623,"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/set","display_name":"Set (abstract data type)","score":0.6337000131607056},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5867999792098999},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5644999742507935},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5410000085830688},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5246999859809875},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4855000078678131}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7608000040054321},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6337000131607056},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5867999792098999},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5644999742507935},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5410000085830688},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5246999859809875},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4855000078678131},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42820000648498535},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3935000002384186},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.388700008392334},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3125},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.2784000039100647},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.25290000438690186}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.00039","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2503.07979","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.07979","pdf_url":"https://arxiv.org/pdf/2503.07979","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":"doi:10.48550/arxiv.2503.07979","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2503.07979","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.07979","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.07979","pdf_url":"https://arxiv.org/pdf/2503.07979","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/G2478649345","display_name":null,"funder_award_id":"24511103100","funder_id":"https://openalex.org/F4320321885","funder_display_name":"Science and Technology Commission of Shanghai Municipality"},{"id":"https://openalex.org/G8051001991","display_name":null,"funder_award_id":"62472098","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/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Class-incremental":[0],"learning":[1],"(CIL)":[2],"enables":[3],"models":[4],"to":[5,52,94,108,136,173],"learn":[6],"new":[7,176],"classes":[8],"progressively":[9],"while":[10],"preserving":[11],"knowledge":[12],"of":[13,39,83,123,129,161,167],"previously":[14],"learned":[15],"ones.":[16],"Recent":[17],"advances":[18],"in":[19,121],"this":[20,65,75],"field":[21],"have":[22],"shifted":[23],"towards":[24],"parameter-efficient":[25,204],"fine-tuning":[26,205],"techniques,":[27],"with":[28],"many":[29],"approaches":[30],"building":[31],"upon":[32],"the":[33,95,99,106,127,134,165,187],"framework":[34],"that":[35,73],"maintains":[36],"a":[37,69,80,145,158,175,198,202],"pool":[38,54],"learnable":[40],"prompts.":[41],"Although":[42],"effective,":[43],"these":[44],"methods":[45],"introduce":[46],"substantial":[47],"computational":[48,119],"overhead,":[49],"primarily":[50],"due":[51],"prompt":[53,62,138],"querying":[55],"and":[56,112,126],"increased":[57],"input":[58],"sequence":[59],"lengths":[60,139],"from":[61],"concatenation.":[63],"In":[64],"work,":[66],"we":[67],"present":[68],"novel":[70],"prompt-based":[71,177],"approach":[72],"addresses":[74],"limitation.":[76],"Our":[77],"method":[78,196],"trains":[79],"single":[81],"set":[82],"shared":[84],"prompts":[85,93,107],"across":[86,157],"all":[87],"tasks":[88],"and,":[89],"rather":[90],"than":[91],"concatenating":[92],"input,":[96],"directly":[97],"modifies":[98],"CLS":[100],"token's":[101],"attention":[102],"computation":[103],"by":[104],"adding":[105],"it.":[109],"This":[110],"simple":[111],"lightweight":[113],"design":[114],"not":[115],"only":[116],"significantly":[117],"reduces":[118],"complexity-both":[120],"terms":[122],"inference":[124],"costs":[125],"number":[128],"trainable":[130],"parameters-but":[131],"also":[132,190],"eliminates":[133],"need":[135],"optimize":[137],"for":[140,151,201],"different":[141],"downstream":[142],"tasks,":[143],"offering":[144],"more":[146],"efficient":[147],"yet":[148],"powerful":[149],"solution":[150],"rehearsal-free":[152],"class-incremental":[153],"learning.":[154],"Extensive":[155],"experiments":[156,181],"diverse":[159],"range":[160],"CIL":[162,178,188],"benchmarks":[163,185],"demonstrate":[164],"effectiveness":[166],"our":[168,195],"approach,":[169],"highlighting":[170],"its":[171],"potential":[172],"establish":[174],"paradigm.":[179],"Furthermore,":[180],"on":[182],"general":[183,203],"recognition":[184],"beyond":[186],"setting":[189],"show":[191],"strong":[192],"performance,":[193],"positioning":[194],"as":[197],"promising":[199],"candidate":[200],"approach.":[206]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
