{"id":"https://openalex.org/W4409365226","doi":"https://doi.org/10.1609/aaai.v39i12.33471","title":"Refine then Classify: Robust Graph Neural Networks with Reliable Neighborhood Contrastive Refinement","display_name":"Refine then Classify: Robust Graph Neural Networks with Reliable Neighborhood Contrastive Refinement","publication_year":2025,"publication_date":"2025-04-11","ids":{"openalex":"https://openalex.org/W4409365226","doi":"https://doi.org/10.1609/aaai.v39i12.33471"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v39i12.33471","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v39i12.33471","pdf_url":null,"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://doi.org/10.1609/aaai.v39i12.33471","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045720576","display_name":"Shuman Zhuang","orcid":"https://orcid.org/0009-0007-1106-1764"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shuman Zhuang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023510892","display_name":"Zhihao Wu","orcid":"https://orcid.org/0000-0001-5835-9903"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhihao Wu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084849129","display_name":"Zhaoliang Chen","orcid":"https://orcid.org/0000-0002-7832-908X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaoliang Chen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072659343","display_name":"Hong\u2010Ning Dai","orcid":"https://orcid.org/0000-0001-6165-4196"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong-Ning Dai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058120371","display_name":"Ximeng Liu","orcid":"https://orcid.org/0000-0002-4238-3295"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ximeng Liu","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5045720576"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1275,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.94894614,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"39","issue":"12","first_page":"13473","last_page":"13482"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9927999973297119,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9927999973297119,"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":0.9891999959945679,"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/T10320","display_name":"Neural Networks and Applications","score":0.9876000285148621,"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":0.6034718751907349},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.500281572341919},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44300779700279236},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.376740038394928}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6034718751907349},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.500281572341919},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44300779700279236},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.376740038394928}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v39i12.33471","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v39i12.33471","pdf_url":null,"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.v39i12.33471","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v39i12.33471","pdf_url":null,"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Graph":[0,70],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4,16,61],"exhibited":[5],"remarkable":[6],"capabilities":[7],"for":[8],"dealing":[9],"with":[10,144],"graph-structured":[11],"data.":[12],"However,":[13,80],"recent":[14],"studies":[15],"revealed":[17],"their":[18],"fragility":[19],"to":[20,26,41,66,75,90,113,124,136,157,192],"adversarial":[21,36,100,158,197],"attacks,":[22],"where":[23],"imperceptible":[24],"perturbations":[25],"the":[27,67,92,97,115,122,148,180,187],"graph":[28],"structure":[29],"can":[30,150],"easily":[31],"mislead":[32],"predictions.":[33],"To":[34,102],"enhance":[35,114],"robustness,":[37],"some":[38],"methods":[39,74,82],"attempt":[40],"learn":[42,151],"robust":[43,152],"representation":[44],"through":[45],"improving":[46],"GNN":[47,166],"architectures.":[48],"Subsequently,":[49],"another":[50],"approach":[51],"suggests":[52],"that":[53,154],"these":[54,104],"GNNs":[55],"might":[56],"taint":[57],"feature":[58],"information":[59],"and":[60,140],"poor":[62],"classifier":[63],"performance,":[64],"leading":[65],"introduction":[68],"of":[69,99,117,176,182,189],"Contrastive":[71],"Learning":[72],"(GCL)":[73],"build":[76],"a":[77,108,128,145,172],"refining-classifying":[78],"pipeline.":[79],"existing":[81],"focus":[83,123],"on":[84],"global-local":[85],"contrastive":[86,131],"strategies,":[87],"which":[88],"fails":[89],"address":[91,103],"robustness":[93,116],"issues":[94],"inherent":[95],"in":[96],"contexts":[98],"robustness.":[101],"challenges,":[105],"we":[106,161],"propose":[107],"novel":[109],"paradigm":[110],"named":[111],"GRANCE":[112,190],"learned":[118],"representations":[119,153],"by":[120],"shifting":[121],"local":[125,138],"neighborhoods.":[126],"Specifically,":[127],"dual":[129],"neighborhood":[130],"learning":[132],"strategy":[133,149],"is":[134],"designed":[135],"extract":[137],"topological":[139],"semantic":[141],"information.":[142],"Paired":[143],"neighbor":[146],"estimator,":[147],"are":[155],"resilient":[156],"edges.":[159],"Additionally,":[160],"also":[162],"provide":[163,171],"an":[164],"improved":[165],"as":[167],"classifier.":[168],"Theoretical":[169],"analyses":[170],"stricter":[173],"lower":[174],"bound":[175],"mutual":[177],"information,":[178],"ensuring":[179],"convergence":[181],"GRANCE.":[183],"Extensive":[184],"experiments":[185],"validate":[186],"effectiveness":[188],"compared":[191],"state-of-the-art":[193],"baselines":[194],"against":[195],"various":[196],"attacks.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}