{"id":"https://openalex.org/W7138344794","doi":"https://doi.org/10.1609/aaai.v40i31.39879","title":"Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning","display_name":"Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138344794","doi":"https://doi.org/10.1609/aaai.v40i31.39879"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i31.39879","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i31.39879","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39879/43840","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/39879/43840","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129722695","display_name":"Yingxu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113480","display_name":"Mohamed bin Zayed University of Artificial Intelligence","ror":"https://ror.org/0258gkt32","country_code":"AE","type":"education","lineage":["https://openalex.org/I4210113480"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Yingxu Wang","raw_affiliation_strings":["Mohamed bin Zayed University of Artificial Intelligence"],"affiliations":[{"raw_affiliation_string":"Mohamed bin Zayed University of Artificial Intelligence","institution_ids":["https://openalex.org/I4210113480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129647476","display_name":"Mengzhu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengzhu Wang","raw_affiliation_strings":["Hebei University of Technology"],"affiliations":[{"raw_affiliation_string":"Hebei University of Technology","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129640836","display_name":"Zhichao Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I82401606","display_name":"Jubail Industrial College","ror":"https://ror.org/01rw40d12","country_code":"SA","type":"education","lineage":["https://openalex.org/I82401606"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Zhichao Huang","raw_affiliation_strings":["JD Industrial, Inc"],"affiliations":[{"raw_affiliation_string":"JD Industrial, Inc","institution_ids":["https://openalex.org/I82401606"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107896135","display_name":"Suyu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Suyu Liu","raw_affiliation_strings":["Nanyang Technological University"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129685993","display_name":"Nan Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Nan Yin","raw_affiliation_strings":["Hong Kong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5129722695"],"corresponding_institution_ids":["https://openalex.org/I4210113480"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55888651,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"31","first_page":"26697","last_page":"26705"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.5724999904632568,"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":0.5724999904632568,"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":0.2117999941110611,"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":0.08959999680519104,"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/domain-adaptation","display_name":"Domain adaptation","score":0.6468999981880188},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5863000154495239},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4814000129699707},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4553999900817871},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.453900009393692},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4147000014781952},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.40139999985694885},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.38690000772476196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7784000039100647},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6468999981880188},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5863000154495239},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5580999851226807},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.477400004863739},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4147000014781952},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.40139999985694885},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3700000047683716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3601999878883362},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.35929998755455017},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35580000281333923},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33480000495910645},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3197999894618988},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C110893760","wikidata":"https://www.wikidata.org/wiki/Q3115590","display_name":"Named graph","level":5,"score":0.2574000060558319},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i31.39879","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i31.39879","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39879/43840","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.v40i31.39879","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i31.39879","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39879/43840","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":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138344794.pdf","grobid_xml":"https://content.openalex.org/works/W7138344794.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graph":[0,78],"Domain":[1],"Adaptation":[2],"(GDA)":[3],"facilitates":[4],"knowledge":[5],"transfer":[6],"from":[7],"labeled":[8],"source":[9,44,167,193],"graphs":[10,14],"to":[11,136,161,180],"unlabeled":[12],"target":[13,134],"by":[15,103],"learning":[16],"domain-invariant":[17],"representations,":[18],"which":[19,46,129],"is":[20,55,177],"essential":[21],"in":[22,49,107,128,165],"applications":[23],"such":[24],"as":[25],"molecular":[26],"property":[27],"prediction":[28],"and":[29,64,100,154],"social":[30],"network":[31],"analysis.":[32],"However,":[33],"most":[34],"existing":[35],"GDA":[36],"methods":[37,214],"rely":[38],"on":[39,205],"the":[40,108,113,138,141,155,162,166,182,190,197,200],"assumption":[41],"of":[42,115,140,185,192,199],"clean":[43],"labels,":[45],"rarely":[47],"holds":[48],"real-world":[50],"scenarios":[51],"where":[52],"annotation":[53],"noise":[54,59,153],"pervasive.":[56],"This":[57,175],"label":[58,217],"severely":[60],"impairs":[61],"feature":[62,109],"alignment":[63],"degrades":[65],"adaptation":[66,89,139,201],"performance":[67],"under":[68,189,215],"domain":[69,88,120],"shifts.":[70],"To":[71,118],"address":[72],"this":[73],"challenge,":[74],"we":[75],"propose":[76],"Nested":[77],"Pseudo-Label":[79],"Refinement":[80],"(NeGPR),":[81],"a":[82,124,171],"novel":[83],"framework":[84],"tailored":[85],"for":[86],"graph-level":[87],"with":[90],"noisy":[91,116,163],"labels.":[92],"NeGPR":[93,122,169,210],"first":[94],"pretrains":[95],"dual":[96],"branches,":[97,102],"i.e.,":[98],"semantic":[99],"topology":[101],"enforcing":[104],"neighborhood":[105],"consistency":[106],"space,":[110],"thereby":[111],"reducing":[112],"influence":[114],"supervision.":[117],"bridge":[119],"gaps,":[121],"employs":[123],"nested":[125],"refinement":[126],"mechanism":[127],"one":[130],"branch":[131],"selects":[132],"high-confidence":[133],"samples":[135],"guide":[137],"other,":[142],"enabling":[143],"progressive":[144],"cross-domain":[145],"learning.":[146],"Furthermore,":[147],"since":[148],"pseudo-labels":[149],"may":[150],"still":[151],"contain":[152],"pre-trained":[156],"branches":[157],"are":[158],"already":[159],"overfitted":[160],"labels":[164],"domain,":[168],"incorporates":[170],"noise-aware":[172],"regularization":[173,176],"strategy.":[174],"theoretically":[178],"proven":[179],"mitigate":[181],"adverse":[183],"effects":[184],"pseudo-label":[186],"noise,":[187],"even":[188],"presence":[191],"overfitting,":[194],"thus":[195],"enhancing":[196],"robustness":[198],"process.":[202],"Extensive":[203],"experiments":[204],"benchmark":[206],"datasets":[207],"demonstrate":[208],"that":[209],"consistently":[211],"outperforms":[212],"state-of-the-art":[213],"severe":[216],"noise.":[218]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}
