{"id":"https://openalex.org/W7220730652","doi":"https://doi.org/10.48550/arxiv.2610.06147","title":"Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts","display_name":"Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts","publication_year":2026,"publication_date":"2026-10-05","ids":{"openalex":"https://openalex.org/W7220730652","doi":"https://doi.org/10.48550/arxiv.2610.06147"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.06147","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06147","pdf_url":"https://arxiv.org/pdf/2610.06147","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.06147","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5157669794","display_name":"Seungmin Oh","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Oh, Seungmin","raw_affiliation_strings":["Ajou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ajou University","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134352085","display_name":"Seunghun Kang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kang, Seunghun","raw_affiliation_strings":["Ajou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ajou University","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038404116","display_name":"Jongbin Ryu","orcid":"https://orcid.org/0000-0001-5574-5358","observed_orcids":["https://orcid.org/0000-0001-5574-5358"]},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ryu, Jongbin","raw_affiliation_strings":["Ajou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ajou University","institution_ids":["https://openalex.org/I57664883"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I57664883"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":1.0,"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":1.0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":9.999999747378752e-05,"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":0.0,"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/test-time-adaptation","display_name":"test-time adaptation","score":0.996999979019165},{"id":"https://openalex.org/keywords/vision-language-models","display_name":"vision-language models","score":0.9909999966621399},{"id":"https://openalex.org/keywords/candidate-verification","display_name":"candidate verification","score":0.9520000219345093},{"id":"https://openalex.org/keywords/memory-bank","display_name":"memory bank","score":0.5789999961853027},{"id":"https://openalex.org/keywords/training-free-adaptation","display_name":"training-free adaptation","score":0.6740000247955322},{"id":"https://openalex.org/keywords/zero-shot-classification","display_name":"zero-shot classification","score":0.6610000133514404},{"id":"https://openalex.org/keywords/domain-generalization","display_name":"domain generalization","score":0.9819999933242798},{"id":"https://openalex.org/keywords/few-shot-classification","display_name":"few-shot classification","score":0.9700000286102295},{"id":"https://openalex.org/keywords/cross-dataset-evaluation","display_name":"cross-dataset evaluation","score":0.8009999990463257},{"id":"https://openalex.org/keywords/inference-efficiency","display_name":"inference efficiency","score":0.45899999141693115}],"concepts":[{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.680899977684021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.65420001745224},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6182000041007996},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6054999828338623},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5745000243186951},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46389999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4593999981880188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43209999799728394},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4138999879360199},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.39570000767707825},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36059999465942383},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32179999351501465},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3158000111579895},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.28999999165534973},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.2549999952316284},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.06147","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06147","pdf_url":"https://arxiv.org/pdf/2610.06147","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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.2610.06147","doi":"https://doi.org/10.48550/arxiv.2610.06147","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.06147","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.06147","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.06147","pdf_url":"https://arxiv.org/pdf/2610.06147","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3812690899","display_name":null,"funder_award_id":"RS-2023","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G7127152209","display_name":null,"funder_award_id":"RS-2023-00255968","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G7241344044","display_name":null,"funder_award_id":"RS-2023-00255968","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G8403091743","display_name":null,"funder_award_id":"IITP-2026-RS-2023-00255968","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"}],"funders":[{"id":"https://openalex.org/F4320322093","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220730652.pdf","grobid_xml":"https://content.openalex.org/works/W7220730652.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4411871887","https://openalex.org/W7127203677","https://openalex.org/W4416236042","https://openalex.org/W4415795202","https://openalex.org/W4415191907","https://openalex.org/W7155526265","https://openalex.org/W4415540175","https://openalex.org/W6910720302","https://openalex.org/W7106335552","https://openalex.org/W4413146132"],"abstract_inverted_index":{"Vision-language":[0],"models":[1],"(VLMs)":[2],"achieve":[3],"strong":[4],"zero-shot":[5,200],"transferability":[6],"but":[7],"remain":[8],"vulnerable":[9],"to":[10,37,133,222,233],"target-domain":[11],"shifts":[12],"at":[13],"inference":[14],"time.":[15],"Test-time":[16],"adaptation":[17,31],"(TTA)":[18],"offers":[19],"a":[20,29,56,74,80,87,101,113,151,187],"practical":[21],"remedy,":[22],"yet":[23],"most":[24],"existing":[25],"VLM-TTA":[26,61,217],"methods":[27,218],"follow":[28],"prediction-side":[30],"paradigm.":[32],"They":[33],"use":[34],"test":[35,88,143],"samples":[36],"adjust":[38],"logits,":[39],"prototypes,":[40],"caches,":[41],"priors,":[42],"or":[43],"feature":[44,89,105],"statistics,":[45],"often":[46],"incurring":[47],"additional":[48],"computational":[49],"overhead.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54],"take":[55],"different":[57],"perspective":[58],"and":[59,90,116,130,185,195,208,231],"reframe":[60],"as":[62,100],"candidate":[63,93,98,128,147,171],"verification":[64],"rather":[65],"than":[66,239],"prediction":[67,167],"adjustment.":[68],"We":[69],"propose":[70],"Test-Time":[71],"Correction":[72],"(TTC),":[73],"hypothesis-based":[75],"correction":[76],"framework":[77],"guided":[78],"by":[79,168],"simple":[81],"principle:":[82],"hypothesize,":[83],"reconstruct,":[84],"correct.":[85],"Given":[86],"its":[91,131],"top-k":[92],"labels,":[94],"TTC":[95,163,211],"treats":[96],"each":[97],"label":[99],"hypothesis,":[102],"reconstructs":[103],"the":[104,107,118,127,138,142,159,166,170,173,240],"within":[106],"corresponding":[108],"latent":[109],"subspace":[110,129,160],"stored":[111],"in":[112],"memory":[114,229,237],"bank,":[115],"measures":[117],"resulting":[119],"divergence":[120,176],"shift.":[121,177],"This":[122,178],"shift":[123],"quantifies":[124],"how":[125],"much":[126],"relations":[132],"other":[134],"candidates":[135],"change":[136],"after":[137],"hypothetical":[139],"insertion":[140],"of":[141],"feature.":[144],"A":[145],"correct":[146],"hypothesis":[148],"induces":[149],"only":[150],"small":[152],"shift,":[153],"whereas":[154],"an":[155],"incorrect":[156],"one":[157],"perturbs":[158],"more":[161],"strongly.":[162],"therefore":[164],"corrects":[165],"selecting":[169],"with":[172],"minimum":[174],"aggregated":[175],"training-free":[179,242],"candidate-verification":[180],"mechanism":[181],"avoids":[182],"iterative":[183],"optimization":[184],"provides":[186],"favorable":[188],"accuracy-efficiency":[189],"trade-off.":[190],"Across":[191],"five":[192],"TTA":[193],"settings":[194],"15":[196],"benchmark":[197],"datasets,":[198],"including":[199],"classification,":[201,205],"domain":[202],"generalization,":[203,207],"few-shot":[204],"base-to-novel":[206],"cross-dataset":[209],"evaluation,":[210],"consistently":[212],"improves":[213],"accuracy":[214],"over":[215,225],"state-of-the-art":[216],"while":[219],"achieving":[220],"up":[221,232],"2x":[223],"speedup,":[224],"3x":[226],"lower":[227,235],"CPU":[228],"usage,":[230],"1.4x":[234],"GPU":[236],"usage":[238],"lowest-memory":[241],"baseline.":[243]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-07T00:00:00"}
