{"id":"https://openalex.org/W7135186984","doi":"https://doi.org/10.48550/arxiv.2603.11201","title":"Representation Finetuning for Continual Learning","display_name":"Representation Finetuning for Continual Learning","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7135186984","doi":"https://doi.org/10.48550/arxiv.2603.11201"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.11201","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11201","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.11201","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129041968","display_name":"Haihua Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Luo, Haihua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129051571","display_name":"Xuming Ran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ran, Xuming","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129100256","display_name":"Tommi K\u00e4rkk\u00e4inen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"K\u00e4rkk\u00e4inen, Tommi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083898002","display_name":"Huiyan Xue","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Huiyan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129018883","display_name":"Zhonghua Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhonghua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129082899","display_name":"Qi Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Qi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128976107","display_name":"Fengyu Cong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cong, Fengyu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5129041968"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9642999768257141,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9642999768257141,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.00419999985024333,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.002099999925121665,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.671500027179718},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5192000269889832},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5188999772071838},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.48249998688697815},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47429999709129333},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4212000072002411},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.38040000200271606},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3601999878883362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7401999831199646},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.671500027179718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6029999852180481},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5899999737739563},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5192000269889832},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5188999772071838},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.48249998688697815},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47429999709129333},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.38040000200271606},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26980000734329224},{"id":"https://openalex.org/C114073186","wikidata":"https://www.wikidata.org/wiki/Q2631895","display_name":"Automated planning and scheduling","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.11201","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11201","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.11201","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11201","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"world":[1],"is":[2],"inherently":[3],"dynamic,":[4],"and":[5,67,179],"continual":[6,26,71,151,183],"learning":[7,72,118,152],"aims":[8],"to":[9,12,14,32,35,62,64,98,138],"enable":[10],"models":[11,20],"adapt":[13,33],"ever-evolving":[15],"data":[16],"streams.":[17],"While":[18],"pre-trained":[19],"have":[21],"shown":[22],"powerful":[23],"performance":[24],"in":[25,70],"learning,":[27],"they":[28],"still":[29],"require":[30],"finetuning":[31,93,173],"effectively":[34],"downstream":[36],"tasks.":[37],"However,":[38],"prevailing":[39],"Parameter-Efficient":[40],"Fine-Tuning":[41],"(PEFT)":[42],"methods":[43],"operate":[44],"through":[45],"empirical,":[46],"black-box":[47],"optimization":[48],"at":[49],"the":[50,88,92],"weight":[51,96],"level.":[52],"These":[53],"approaches":[54],"lack":[55],"explicit":[56,121],"control":[57],"over":[58],"representation":[59,99,172],"drift,":[60],"leading":[61],"sensitivity":[63],"domain":[65],"shifts":[66,91],"catastrophic":[68],"forgetting":[69],"scenarios.":[73],"In":[74],"this":[75],"work,":[76],"we":[77],"introduce":[78],"Continual":[79],"Representation":[80],"Learning":[81],"(CoRe),":[82],"a":[83,109,117,139,175],"novel":[84],"framework":[85],"that":[86,155],"for":[87,126,132,182],"first":[89],"time":[90],"paradigm":[94,181],"from":[95],"space":[97],"space.":[100],"Unlike":[101],"conventional":[102],"methods,":[103],"CoRe":[104,142,156],"performs":[105],"task-specific":[106],"interventions":[107],"within":[108],"low-rank":[110,140],"linear":[111],"subspace":[112],"of":[113],"hidden":[114],"representations,":[115],"adopting":[116],"process":[119],"with":[120],"objectives,":[122],"which":[123],"ensures":[124],"stability":[125],"past":[127],"tasks":[128],"while":[129],"maintaining":[130],"plasticity":[131],"new":[133],"ones.":[134],"By":[135],"constraining":[136],"updates":[137],"subspace,":[141],"achieves":[143],"exceptional":[144],"parameter":[145,160],"efficiency.":[146],"Extensive":[147],"experiments":[148],"across":[149],"multiple":[150],"benchmarks":[153],"demonstrate":[154],"not":[157],"only":[158],"preserves":[159],"efficiency":[161],"but":[162],"also":[163],"significantly":[164],"outperforms":[165],"existing":[166],"state-of-the-art":[167],"methods.":[168],"Our":[169],"work":[170],"introduces":[171],"as":[174],"new,":[176],"more":[177],"effective":[178],"interpretable":[180],"learning.":[184]},"counts_by_year":[],"updated_date":"2026-03-14T06:46:50.379900","created_date":"2026-03-14T00:00:00"}