{"id":"https://openalex.org/W7137943343","doi":"https://doi.org/10.1609/aaai.v40i31.39842","title":"Self-Supervised Contrastive Re-Learning for Multi-Graph Multi-Label Classification","display_name":"Self-Supervised Contrastive Re-Learning for Multi-Graph Multi-Label Classification","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137943343","doi":"https://doi.org/10.1609/aaai.v40i31.39842"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i31.39842","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i31.39842","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39842/43803","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/39842/43803","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129743997","display_name":"Meixia Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":true,"raw_author_name":"Meixia Wang","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129747674","display_name":"Yuhai Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Yuhai Zhao","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020485549","display_name":"Zhengkui Wang","orcid":"https://orcid.org/0000-0003-4554-0791"},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Zhengkui Wang","raw_affiliation_strings":["Singapore Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065454380","display_name":"Yejiang Wang","orcid":"https://orcid.org/0000-0001-7908-4275"},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Yejiang Wang","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035886819","display_name":"Miaomiao Huang","orcid":"https://orcid.org/0000-0002-8845-1310"},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Miaomiao Huang","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129661445","display_name":"Fenglong Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fenglong Ma","raw_affiliation_strings":["Pennsylvania State University"],"affiliations":[{"raw_affiliation_string":"Pennsylvania State University","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031382096","display_name":"Fazal Wahab","orcid":"https://orcid.org/0000-0001-9684-3392"},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Fazal Wahab","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101576537","display_name":"Wen Shan","orcid":"https://orcid.org/0000-0002-7377-8943"},"institutions":[{"id":"https://openalex.org/I8696757","display_name":"Singapore University of Social Sciences","ror":"https://ror.org/01s57k749","country_code":"SG","type":"education","lineage":["https://openalex.org/I8696757"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wen Shan","raw_affiliation_strings":["Singapore University of Social Sciences"],"affiliations":[{"raw_affiliation_string":"Singapore University of Social Sciences","institution_ids":["https://openalex.org/I8696757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129724193","display_name":"Xingwei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I87182695","display_name":"Universidad del Noreste","ror":"https://ror.org/02ahky613","country_code":"MX","type":"education","lineage":["https://openalex.org/I87182695"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Xingwei Wang","raw_affiliation_strings":["Northeastern University"],"affiliations":[{"raw_affiliation_string":"Northeastern University","institution_ids":["https://openalex.org/I87182695"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5129743997"],"corresponding_institution_ids":["https://openalex.org/I87182695"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1542686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"31","first_page":"26363","last_page":"26371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.8824999928474426,"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":0.8824999928474426,"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":0.033900000154972076,"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":0.015799999237060547,"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/discriminative-model","display_name":"Discriminative model","score":0.6521000266075134},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4350000023841858},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41830000281333923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41179999709129333},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4106999933719635},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.39419999718666077},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3393000066280365},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.320499986410141},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3167000114917755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6873999834060669},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6583999991416931},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6521000266075134},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5131999850273132},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4350000023841858},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41830000281333923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41179999709129333},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4106999933719635},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.39419999718666077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34380000829696655},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3393000066280365},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2874000072479248},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2770000100135803},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i31.39842","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i31.39842","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39842/43803","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.v40i31.39842","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i31.39842","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/39842/43803","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":[{"id":"https://metadata.un.org/sdg/10","score":0.782854437828064,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G7797178789","display_name":null,"funder_award_id":"62432003","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"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7137943343.pdf","grobid_xml":"https://content.openalex.org/works/W7137943343.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-graph":[0],"multi-label":[1,173],"learning":[2,27],"(MGML)":[3],"represents":[4],"each":[5],"object":[6],"as":[7],"a":[8,91,109,128,157],"bag-of-graphs":[9],"with":[10,120],"multiple":[11],"labels,":[12],"but":[13,77],"demands":[14],"large-scale":[15],"labeled":[16],"data":[17,34],"whose":[18],"acquisition":[19],"is":[20],"often":[21],"difficult":[22],"and":[23,117,147,194],"costly.":[24],"Self-supervised":[25],"contrastive":[26,93,130,158],"(SCL)":[28],"mitigates":[29],"label":[30,68,83,104,111,115,137],"dependence":[31],"by":[32,61,139],"leveraging":[33],"augmentation":[35],"to":[36,49,102,113,151,165],"construct":[37],"discriminative":[38],"pretext":[39],"tasks,":[40],"proving":[41],"effective":[42],"for":[43,96],"multi-instance":[44],"learning.":[45],"However,":[46],"when":[47],"applied":[48],"MGML,":[50],"SCL":[51],"faces":[52],"two":[53],"key":[54],"challenges:":[55],"(1)":[56],"it":[57,71],"distinguishes":[58],"individual":[59],"instances":[60],"their":[62],"differences,":[63],"whereas":[64],"MGML":[65,81],"requires":[66],"modeling":[67],"correlations;":[69],"(2)":[70],"assumes":[72],"semantic":[73,153],"invariance":[74],"under":[75],"augmentation,":[76],"structural":[78,176],"perturbations":[79],"in":[80],"alter":[82],"semantics.":[84],"To":[85],"tackle":[86],"these":[87,133],"challenges,":[88],"we":[89,106,155],"propose":[90],"self-suPervised":[92],"rE-learning":[94],"framework":[95],"mulTi-grAph":[97],"multi-labeL":[98],"classification":[99],"(PETAL).":[100],"Specifically,":[101],"model":[103],"correlations,":[105],"first":[107],"define":[108],"unified":[110],"space":[112],"learn":[114],"prototypes":[116],"align":[118],"features":[119],"them,":[121],"yielding":[122],"prototype-aligned":[123,163],"representations.":[124],"We":[125],"then":[126],"design":[127],"multi-granularity":[129],"loss":[131],"over":[132,191],"representations,":[134],"which":[135],"captures":[136],"dependencies":[138],"contrasting":[140],"at":[141],"the":[142],"bag":[143],"level,":[144,146],"graph":[145],"bag-graph":[148],"level.":[149],"Moreover,":[150],"ensure":[152],"invariance,":[154],"develop":[156],"re-learning":[159],"strategy":[160],"based":[161],"on":[162,179],"representations":[164],"generate":[166],"augmentation-free":[167],"positive":[168],"samples.":[169],"This":[170],"guarantees":[171],"consistent":[172],"distributions":[174],"without":[175],"perturbations.":[177],"Experiments":[178],"six":[180],"datasets":[181],"demonstrate":[182],"that":[183],"PETAL":[184],"achieves":[185],"an":[186],"average":[187],"improvement":[188],"of":[189],"4.12%":[190],"state-of-the-art":[192],"self-supervised":[193],"supervised":[195],"baselines.":[196]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-03-18T00:00:00"}