{"id":"https://openalex.org/W7129737091","doi":"https://doi.org/10.1109/tpami.2026.3665813","title":"Learning Compact Semantic Information and Reliable Pseudo-Labels for Incomplete Multi-View Multi-Label Classification","display_name":"Learning Compact Semantic Information and Reliable Pseudo-Labels for Incomplete Multi-View Multi-Label Classification","publication_year":2026,"publication_date":"2026-02-17","ids":{"openalex":"https://openalex.org/W7129737091","doi":"https://doi.org/10.1109/tpami.2026.3665813","pmid":"https://pubmed.ncbi.nlm.nih.gov/41701604"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2026.3665813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3665813","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/A5100330474","display_name":"Yi Liu","orcid":"https://orcid.org/0000-0001-9701-6460"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yadong Liu","raw_affiliation_strings":["Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0000-9855-7744","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063403522","display_name":"Chengliang Liu","orcid":"https://orcid.org/0000-0001-5983-8981"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengliang Liu","raw_affiliation_strings":["Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-5983-8981","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126190000","display_name":"Jie Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wen","raw_affiliation_strings":["Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9554-2379","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126246660","display_name":"Li Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Shen","raw_affiliation_strings":["School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-5659-3464","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126255567","display_name":"Bob Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Bob Zhang","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau, Taipa, China"],"raw_orcid":"https://orcid.org/0000-0003-2497-9519","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau, Taipa, China","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100755964","display_name":"Ying Xu","orcid":"https://orcid.org/0000-0002-2401-7718"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Xu","raw_affiliation_strings":["Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-0530-2123","affiliations":[{"raw_affiliation_string":"Shenzhen Key Laboratory of Visual Object Detection and Recognition, Harbin Institute of Technology, Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":24.2102,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.99068106,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"48","issue":"7","first_page":"7575","last_page":"7589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9613999724388123,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9613999724388123,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.008200000040233135,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.00419999985024333,"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/leverage","display_name":"Leverage (statistics)","score":0.6381999850273132},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4758000075817108},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42899999022483826},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4259999990463257},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3917999863624573},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3797999918460846},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.37860000133514404},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3634999990463257},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.3614000082015991}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7843999862670898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.660099983215332},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6381999850273132},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5735999941825867},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4758000075817108},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42899999022483826},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4259999990463257},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3917999863624573},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3614000082015991},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34450000524520874},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C113336015","wikidata":"https://www.wikidata.org/wiki/Q574010","display_name":"Complete information","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C156201811","wikidata":"https://www.wikidata.org/wiki/Q5418360","display_name":"Evidential reasoning approach","level":4,"score":0.30230000615119934},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2867000102996826},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2770000100135803},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C2776207758","wikidata":"https://www.wikidata.org/wiki/Q5303302","display_name":"Downstream (manufacturing)","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2026.3665813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2026.3665813","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:41701604","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41701604","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/G1973322159","display_name":null,"funder_award_id":"2024A1515030213","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G5618573370","display_name":null,"funder_award_id":"62372136","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/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-view":[0,12],"data":[1,4,86],"encompasses":[2],"various":[3],"types,":[5],"including":[6],"multi-feature,":[7],"multi-sequence,":[8],"and":[9,39,91,205,238],"multi-modal":[10],"data.":[11,119],"multi-label":[13,29,47,75],"classification":[14,30,48,76,193],"aims":[15],"to":[16,26,45,63,78,127,150,157,174,190,200,208],"leverage":[17],"the":[18,35,52,65,80,85,113,117,129,136,151,169,176,202,226],"rich":[19],"semantic":[20,56,130],"information":[21,57,115,131,146],"contained":[22],"in":[23,94,103,213,216,233],"multiple":[24,59,222],"views":[25,38,60,90,163],"achieve":[27],"enhanced":[28],"performance.":[31,218],"In":[32],"practical":[33],"applications,":[34],"absence":[36],"of":[37,100,116,132,229,235],"labels":[40,93],"poses":[41],"a":[42,71,105,123],"significant":[43],"challenge":[44,83],"multi-view":[46,74,81],"tasks.":[49],"Premised":[50],"on":[51,84,221],"assumption":[53],"that":[54,110,147],"shared":[55,133],"across":[58],"is":[61,148,181],"sufficient":[62],"support":[64],"downstream":[66,152],"task,":[67],"we":[68,121,167],"propose":[69],"CTRL,":[70],"novel":[72],"incomplete":[73],"framework":[77],"address":[79],"learning":[82,104,139],"with":[87,184],"partially":[88],"missing":[89,92],"this":[95],"paper.":[96],"The":[97],"core":[98],"mechanism":[99],"CTRL":[101,156],"lies":[102],"high-purity,":[106],"low-redundancy":[107],"condensed":[108],"representation":[109,138],"adequately":[111],"captures":[112],"essential":[114],"original":[118],"Specifically,":[120],"design":[122],"new":[124],"objective":[125],"loss":[126],"enhance":[128],"cross-view":[134],"within":[135],"joint":[137],"process":[140],"while":[141],"simultaneously":[142],"suppressing":[143],"intra-view":[144],"redundant":[145],"irrelevant":[149],"task.":[153],"This":[154,179,196],"enables":[155],"extract":[158],"task-relevant":[159],"representations":[160],"even":[161],"when":[162],"are":[164],"incomplete.":[165],"Furthermore,":[166],"employ":[168],"Beta":[170],"Evidential":[171],"Neural":[172],"Network":[173],"model":[175,189,217,232],"label":[177],"distribution.":[178],"network":[180],"then":[182],"integrated":[183],"Dempster-Shafer":[185],"theory,":[186],"enabling":[187],"our":[188,230],"perform":[191],"label-level":[192],"uncertainty":[194,204],"estimation.":[195],"also":[197],"allows":[198],"us":[199],"use":[201],"estimated":[203],"belief":[206],"mass":[207],"create":[209],"high-reliability":[210],"pseudo-labels,":[211],"resulting":[212],"further":[214],"gains":[215],"Experimental":[219],"results":[220],"benchmark":[223],"datasets":[224],"demonstrate":[225],"superior":[227],"performance":[228],"proposed":[231],"terms":[234],"accuracy,":[236],"robustness,":[237],"reliability.":[239]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-06-06T06:22:57.294733","created_date":"2026-02-18T00:00:00"}
