{"id":"https://openalex.org/W4392251629","doi":"https://doi.org/10.1109/tpami.2024.3370963","title":"Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training","display_name":"Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training","publication_year":2024,"publication_date":"2024-02-28","ids":{"openalex":"https://openalex.org/W4392251629","doi":"https://doi.org/10.1109/tpami.2024.3370963","pmid":"https://pubmed.ncbi.nlm.nih.gov/38416608"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2024.3370963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3370963","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5007736768","display_name":"Yongyi Su","orcid":"https://orcid.org/0009-0001-6911-8256"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongyi Su","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-6911-8256","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451925","display_name":"Xun Xu","orcid":"https://orcid.org/0000-0002-5220-2240"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]},{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Xun Xu","raw_affiliation_strings":["Institute for Infocomm Research (I2R), A*STAR, Singapore","Southwest Jiaotong University, China"],"raw_orcid":"https://orcid.org/0000-0002-5220-2240","affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research (I2R), A*STAR, Singapore","institution_ids":["https://openalex.org/I115228651","https://openalex.org/I3005327000"]},{"raw_affiliation_string":"Southwest Jiaotong University, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070559820","display_name":"Tianrui Li","orcid":"https://orcid.org/0000-0001-7780-104X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Li","raw_affiliation_strings":["Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-7780-104X","affiliations":[{"raw_affiliation_string":"Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065964089","display_name":"Kui Jia","orcid":"https://orcid.org/0000-0003-2661-5700"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kui Jia","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2661-5700","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1909,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.88367974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"46","issue":"8","first_page":"5524","last_page":"5540"},"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":0.9991000294685364,"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":0.9991000294685364,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.995199978351593,"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/T12676","display_name":"Machine Learning and ELM","score":0.9837999939918518,"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/computer-science","display_name":"Computer science","score":0.7292259335517883},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6973841190338135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6629924774169922},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6331436038017273},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5962464809417725},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5553591847419739},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.49953770637512207},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.4574927091598511},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4540378451347351},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3799889087677002},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10417434573173523}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7292259335517883},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6973841190338135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6629924774169922},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6331436038017273},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5962464809417725},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5553591847419739},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.49953770637512207},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.4574927091598511},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4540378451347351},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3799889087677002},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10417434573173523},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2024.3370963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2024.3370963","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:38416608","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38416608","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7436548981","display_name":null,"funder_award_id":"62106078","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/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320334744","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1565327149","https://openalex.org/W2033178790","https://openalex.org/W2104094955","https://openalex.org/W2162651021","https://openalex.org/W2165698076","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2593768305","https://openalex.org/W2746791238","https://openalex.org/W2766897166","https://openalex.org/W2786808285","https://openalex.org/W2963135377","https://openalex.org/W2963524571","https://openalex.org/W2964285681","https://openalex.org/W2964288524","https://openalex.org/W2978625989","https://openalex.org/W2979805229","https://openalex.org/W2984353870","https://openalex.org/W3035519852","https://openalex.org/W3035682985","https://openalex.org/W3035701489","https://openalex.org/W3091002423","https://openalex.org/W3192275354","https://openalex.org/W3192693288","https://openalex.org/W3203098462","https://openalex.org/W3209696639","https://openalex.org/W3214752899","https://openalex.org/W4214715922","https://openalex.org/W4289639938","https://openalex.org/W4293846201","https://openalex.org/W4312365002","https://openalex.org/W4312399508","https://openalex.org/W4312897837","https://openalex.org/W4319300892","https://openalex.org/W4388460234","https://openalex.org/W6633949838","https://openalex.org/W6639480849","https://openalex.org/W6677069268","https://openalex.org/W6680434193","https://openalex.org/W6683633756","https://openalex.org/W6684191040","https://openalex.org/W6687400500","https://openalex.org/W6688325169","https://openalex.org/W6734335776","https://openalex.org/W6746171285","https://openalex.org/W6746282794","https://openalex.org/W6751647823","https://openalex.org/W6757555829","https://openalex.org/W6762913911","https://openalex.org/W6764990469","https://openalex.org/W6773005947","https://openalex.org/W6773992155","https://openalex.org/W6780178746","https://openalex.org/W6784333009","https://openalex.org/W6788125050","https://openalex.org/W6791252336","https://openalex.org/W6800892926","https://openalex.org/W6801756507","https://openalex.org/W6803247036","https://openalex.org/W6804111167","https://openalex.org/W6842760672","https://openalex.org/W6849917780","https://openalex.org/W6850116420"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W2997094352","https://openalex.org/W3216976533","https://openalex.org/W100620283","https://openalex.org/W2495260952","https://openalex.org/W4394050964","https://openalex.org/W2551249631"],"abstract_inverted_index":{"Deploying":[0],"models":[1],"on":[2,39,236],"target":[3,41,135,140,242,252],"domain":[4,31,42,151,167],"data":[5,32,82,183],"subject":[6],"to":[7,19,28,60,92,122,142,146,164,193,197,220],"distribution":[8],"shift":[9],"requires":[10],"adaptation.":[11,148],"Test-time":[12],"training":[13,109],"(TTT)":[14],"emerges":[15],"as":[16,221],"a":[17,23,52,105,116,201,260],"solution":[18],"this":[20,64,256],"adaptation":[21,248],"under":[22,112,226],"realistic":[24,106],"scenario":[25],"where":[26],"access":[27],"full":[29],"source":[30,88,133,144,150,166],"is":[33,43,51,83,90,153,195,206,218],"not":[34],"available,":[35],"and":[36,71,86,134,137,184,214,249,266],"instant":[37],"inference":[38],"the":[40,55,100,139,143,215,233],"required.":[44],"Despite":[45],"many":[46],"efforts":[47],"into":[48],"TTT,":[49],"there":[50],"confusion":[53],"over":[54],"experimental":[56],"settings,":[57],"thus":[58],"leading":[59],"unfair":[61],"comparisons.":[62],"In":[63],"work,":[65],"we":[66,103,114,158,185],"first":[67],"revisit":[68],"TTT":[69,73,194,204,228,238,264],"assumptions":[70],"categorize":[72],"protocols":[74],"by":[75,208],"two":[76],"key":[77],"factors,":[78],"i.e.,":[79],"whether":[80,87],"testing":[81],"sequentially":[84],"streamed":[85],"model":[89,217],"allowed":[91],"be":[93,270],"trained":[94],"with":[95,211],"modified":[96],"loss":[97],"function.":[98],"Among":[99],"multiple":[101],"protocols,":[102,229],"adopt":[104],"sequential":[107],"test-time":[108,117,125],"(sTTT)":[110],"protocol,":[111],"which":[113],"develop":[115,160],"anchored":[118,170,212],"clustering":[119],"(TTAC)":[120],"approach":[121,205],"enable":[123],"stronger":[124],"feature":[126],"learning.":[127],"TTAC":[128],"discovers":[129],"clusters":[130,141],"in":[131,179],"both":[132],"domains":[136],"matches":[138],"ones":[145],"improve":[147],"When":[149],"information":[152],"strictly":[154],"absent":[155],"(i.e.,":[156],"source-free)":[157],"further":[159],"an":[161],"efficient":[162],"method":[163],"infer":[165],"distributions":[168],"for":[169],"clustering.":[171],"Finally,":[172],"self-training":[173,210],"(ST)":[174],"has":[175],"demonstrated":[176],"great":[177],"success":[178],"learning":[180],"from":[181],"unlabeled":[182],"empirically":[186],"figure":[187],"out":[188],"that":[189],"applying":[190],"ST":[191],"alone":[192],"prone":[196],"confirmation":[198],"bias.":[199],"Therefore,":[200],"more":[202],"effective":[203],"introduced":[207],"regularizing":[209],"clustering,":[213],"improved":[216],"referred":[219],"TTAC++.":[222],"We":[223,254],"demonstrate":[224],"that,":[225],"all":[227],"TTAC++":[230],"consistently":[231],"outperforms":[232],"state-of-the-art":[234],"methods":[235],"five":[237],"datasets,":[239],"including":[240],"corrupted":[241],"domain,":[243],"selected":[244],"hard":[245],"samples,":[246],"synthetic-to-real":[247],"adversarially":[250],"attacked":[251],"domain.":[253],"hope":[255],"work":[257],"will":[258],"provide":[259],"fair":[261],"benchmarking":[262],"of":[263],"methods,":[265],"future":[267],"research":[268],"should":[269],"compared":[271],"within":[272],"respective":[273],"protocols.":[274]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}