{"id":"https://openalex.org/W7138313739","doi":"https://doi.org/10.1609/aaai.v40i30.39784","title":"Neighbor-aware Label Refinement: Enhancing Unreliable Instance-Dependent Partial Labels","display_name":"Neighbor-aware Label Refinement: Enhancing Unreliable Instance-Dependent Partial Labels","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138313739","doi":"https://doi.org/10.1609/aaai.v40i30.39784"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i30.39784","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i30.39784","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39784/43745","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39784/43745","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005225786","display_name":"Xijia Tang","orcid":"https://orcid.org/0009-0005-5187-9427"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xijia Tang","raw_affiliation_strings":["National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101102036","display_name":"Yuhua Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142037","display_name":"Shanxi University of Traditional Chinese Medicine","ror":"https://ror.org/0522dg826","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142037"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhua Qian","raw_affiliation_strings":["Shanxi University"],"affiliations":[{"raw_affiliation_string":"Shanxi University","institution_ids":["https://openalex.org/I4210142037"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129655813","display_name":"Chao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Xu","raw_affiliation_strings":["National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129722003","display_name":"Chenping Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenping Hou","raw_affiliation_strings":["National University of Defense Technology"],"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005225786"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.52477357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"30","first_page":"25849","last_page":"25857"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.6184999942779541,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.6184999942779541,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.2930999994277954,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.0071000000461936,"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/ambiguity","display_name":"Ambiguity","score":0.6220999956130981},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5946000218391418},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5521000027656555},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.5254999995231628},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5170000195503235},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.47450000047683716},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.40290001034736633},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38179999589920044}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7185999751091003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7182000279426575},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.6220999956130981},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5946000218391418},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5810999870300293},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5521000027656555},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.5254999995231628},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5170000195503235},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.47450000047683716},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3808000087738037},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3644999861717224},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.36390000581741333},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29019999504089355},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.26409998536109924}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i30.39784","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i30.39784","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39784/43745","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i30.39784","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i30.39784","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39784/43745","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2802911279","display_name":null,"funder_award_id":"Young","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4436210142","display_name":"Center Operations: Center for Land Surface Hazards (CLaSH)","funder_award_id":"2425607","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6896277159","display_name":null,"funder_award_id":"2136005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6918183950","display_name":"Creating a Path to STEM Careers in Psychology for Under-Represented Minorities","funder_award_id":"2136005","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8178587797","display_name":null,"funder_award_id":"62136005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G895001607","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138313739.pdf","grobid_xml":"https://content.openalex.org/works/W7138313739.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Partial":[0,79],"Label":[1,80,96],"Learning":[2,81],"(PLL)":[3],"aims":[4],"to":[5,29,109,119],"train":[6],"multi-class":[7],"classifiers":[8],"from":[9],"examples":[10],"where":[11,53],"each":[12],"instance":[13,137],"is":[14,27],"associated":[15],"with":[16],"a":[17,72,91],"set":[18],"of":[19,179],"candidate":[20,54,112],"labels,":[21],"among":[22,106],"which":[23],"the":[24,64,85,103,148,175,180],"ground-truth":[25,65],"label":[26,113,154],"assumed":[28],"be":[30,157],"included.":[31],"While":[32],"most":[33],"existing":[34],"studies":[35],"assume":[36],"that":[37,153],"partial":[38,140],"labels":[39,121],"are":[40],"both":[41,169],"instance-independent":[42],"and":[43,61,98,115,136,163,171,177],"reliable,":[44],"such":[45],"assumptions":[46],"often":[47],"break":[48],"down":[49],"in":[50,87,139],"real-world":[51,172],"scenarios,":[52],"sets":[55,114],"may":[56],"depend":[57],"on":[58,168],"instance-specific":[59],"features":[60],"even":[62],"exclude":[63],"label.":[66],"In":[67],"this":[68],"work,":[69],"we":[70,89,143],"investigate":[71],"more":[73],"realistic":[74],"setting":[75],"termed":[76],"Unreliable":[77],"Instance-Dependent":[78],"(UIDPLL).":[82],"To":[83],"address":[84],"challenges":[86],"UIDPLL,":[88],"propose":[90],"novel":[92],"framework":[93],"named":[94],"Neighborhood-guided":[95],"Augmentation":[97],"Pruning":[99],"(NLAP).":[100],"NLAP":[101,150],"exploits":[102],"structural":[104],"consistency":[105],"neighboring":[107],"instances":[108],"progressively":[110],"refine":[111],"integrates":[116],"classifier":[117],"feedback":[118],"disambiguate":[120],"during":[122],"training.":[123],"This":[124],"progressive":[125],"mechanism":[126],"improves":[127],"classification":[128],"performance":[129],"by":[130,134],"tackling":[131],"ambiguity":[132,155],"caused":[133],"noise":[135],"dependency":[138],"labels.":[141],"Furthermore,":[142],"provide":[144],"theoretical":[145],"guarantees":[146],"for":[147],"proposed":[149,181],"framework,":[151],"demonstrating":[152],"can":[156],"effectively":[158],"reduced":[159],"through":[160],"appropriate":[161],"refinement":[162],"pruning":[164],"procedures.":[165],"Extensive":[166],"experiments":[167],"benchmark":[170],"datasets":[173],"demonstrate":[174],"robustness":[176],"effectiveness":[178],"method.":[182]},"counts_by_year":[],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2026-03-18T00:00:00"}
