{"id":"https://openalex.org/W7165376541","doi":"https://doi.org/10.48550/arxiv.2606.20196","title":"Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation","display_name":"Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation","publication_year":2026,"publication_date":"2026-06-18","ids":{"openalex":"https://openalex.org/W7165376541","doi":"https://doi.org/10.48550/arxiv.2606.20196"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.20196","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20196","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.20196","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139012316","display_name":"Hyun-Kurl Jang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jang, Hyun-Kurl","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138975684","display_name":"Jihun Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Jihun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059067295","display_name":"Hyeokjun Kweon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kweon, Hyeokjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138967783","display_name":"Kuk-Jin Yoon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoon, Kuk-Jin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":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":0.9210000038146973,"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":0.9210000038146973,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.025699999183416367,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.010200000368058681,"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/adaptation","display_name":"Adaptation (eye)","score":0.6564000248908997},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6377000212669373},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.5805000066757202},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.4596000015735626},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4496000111103058},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3885999917984009},{"id":"https://openalex.org/keywords/open-source","display_name":"Open source","score":0.3630000054836273},{"id":"https://openalex.org/keywords/compounding","display_name":"Compounding","score":0.3610000014305115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7825000286102295},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6564000248908997},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6377000212669373},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.5805000066757202},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.4596000015735626},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4496000111103058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40790000557899475},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3885999917984009},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3772999942302704},{"id":"https://openalex.org/C3018397939","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Open source","level":3,"score":0.3630000054836273},{"id":"https://openalex.org/C207673951","wikidata":"https://www.wikidata.org/wiki/Q1303150","display_name":"Compounding","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.35179999470710754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3465000092983246},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C2778095710","wikidata":"https://www.wikidata.org/wiki/Q6031225","display_name":"Information source (mathematics)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.20196","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20196","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":"doi:10.48550/arxiv.2606.20196","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20196","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":"Preprint"},"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":{"Continual":[0],"Test-Time":[1],"Adaptation":[2],"(CTTA)":[3],"aims":[4],"to":[5,29,40,84,154],"maintain":[6],"model":[7],"performance":[8],"under":[9,43],"evolving":[10],"target":[11,101],"domains":[12],"by":[13],"adapting":[14],"online":[15],"without":[16,160],"labeled":[17],"data.":[18,164],"However,":[19],"practical":[20],"deployments":[21],"often":[22],"cannot":[23],"retain":[24],"the":[25,95,144,149],"source":[26,67,96,120,163],"dataset":[27],"due":[28],"privacy":[30],"or":[31],"licensing":[32],"constraints,":[33],"and":[34,52,72,124,143,157],"purely":[35],"source-free":[36],"CTTA":[37,118,134],"methods":[38],"tend":[39],"become":[41],"unstable":[42],"long-term":[44,138],"distribution":[45],"shift,":[46],"suffering":[47],"from":[48],"compounding":[49],"self-training":[50],"errors":[51],"catastrophic":[53],"forgetting.":[54],"We":[55],"introduce":[56],"DO-ALL":[57,81,127],"(Distill":[58],"Once,":[59],"Adapt":[60],"Life-Long),":[61],"a":[62,70,86,113],"plug-and-play":[63],"framework":[64],"that":[65,93],"revisits":[66],"information":[68],"in":[69],"compact":[71],"privacy-conscious":[73],"form":[74],"via":[75,119],"Dataset":[76],"Distillation":[77],"(DD).":[78],"Before":[79],"deployment,":[80],"performs":[82],"DD":[83,153],"produce":[85],"small":[87],"set":[88],"of":[89,151],"synthetic":[90],"distilled":[91],"anchors":[92],"summarize":[94],"distribution.":[97],"During":[98],"adaptation,":[99],"each":[100],"sample":[102],"is":[103,167],"matched":[104],"with":[105],"its":[106],"most":[107],"semantically":[108],"aligned":[109],"anchor,":[110],"which":[111],"provides":[112],"stable":[114,156],"reference":[115],"for":[116],"various":[117],"replay,":[121],"representation":[122],"alignment,":[123],"manifold-smoothing":[125],"regularization.":[126],"can":[128],"be":[129],"seamlessly":[130],"integrated":[131],"into":[132],"existing":[133],"algorithms,":[135],"consistently":[136],"improving":[137],"robustness":[139],"across":[140],"CIFAR100-C,":[141],"ImageNet-C,":[142],"CCC":[145],"benchmark.":[146],"This":[147],"demonstrates":[148],"potential":[150],"leveraging":[152],"enable":[155],"continuous":[158],"adaptation":[159],"retaining":[161],"raw":[162],"The":[165],"code":[166],"available":[168],"at":[169],"https://github.com/blue-531/DOALL.":[170]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-20T00:00:00"}
