{"id":"https://openalex.org/W7134824003","doi":"https://doi.org/10.48550/arxiv.2603.08137","title":"Mitigating Homophily Disparity in Graph Anomaly Detection: A Scalable and Adaptive Approach","display_name":"Mitigating Homophily Disparity in Graph Anomaly Detection: A Scalable and Adaptive Approach","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134824003","doi":"https://doi.org/10.48550/arxiv.2603.08137"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.08137","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128665911","display_name":"Yunhui Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yunhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086705284","display_name":"Qizhuo Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Qizhuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128649736","display_name":"Yinfeng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yinfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050330142","display_name":"Xudong Jin","orcid":"https://orcid.org/0000-0002-1783-8091"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Xudong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128668598","display_name":"Tao Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043041253","display_name":"Bin Chong","orcid":"https://orcid.org/0000-0002-8741-178X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chong, Bin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128632651","display_name":"Tieke He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Tieke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9563999772071838,"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":0.9563999772071838,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.006300000008195639,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.005100000184029341,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/homophily","display_name":"Homophily","score":0.8476999998092651},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7900000214576721},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49000000953674316},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4185999929904938},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4081000089645386},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.39259999990463257},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.39070001244544983},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.38370001316070557}],"concepts":[{"id":"https://openalex.org/C2779812341","wikidata":"https://www.wikidata.org/wiki/Q5891525","display_name":"Homophily","level":2,"score":0.8476999998092651},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7900000214576721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.619700014591217},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4731000065803528},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4185999929904938},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4081000089645386},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.39070001244544983},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.38370001316070557},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C21424316","wikidata":"https://www.wikidata.org/wiki/Q718621","display_name":"Chebyshev filter","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C38935604","wikidata":"https://www.wikidata.org/wiki/Q4330363","display_name":"Stylized fact","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.2824999988079071},{"id":"https://openalex.org/C48659774","wikidata":"https://www.wikidata.org/wiki/Q4907197","display_name":"Bijection, injection and surjection","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2671000063419342},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.2581000030040741}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.08137","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.08137","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08137","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.08137","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graph":[0],"anomaly":[1],"detection":[2],"(GAD)":[3],"aims":[4],"to":[5,79,141],"identify":[6],"nodes":[7,35,177],"that":[8],"deviate":[9],"from":[10],"normal":[11,147,174],"patterns":[12],"in":[13],"structure":[14],"or":[15],"features.":[16],"While":[17],"recent":[18],"GNN-based":[19],"approaches":[20],"have":[21],"advanced":[22],"this":[23],"task,":[24],"they":[25],"struggle":[26],"with":[27],"two":[28],"major":[29],"challenges:":[30],"1)":[31],"homophily":[32,38,98],"disparity,":[33,99,130],"where":[34],"exhibit":[36],"varying":[37],"at":[39],"both":[40,90],"class":[41],"and":[42,45,65,74,82,88,92,111,156,159,175,190],"node":[43],"levels;":[44],"2)":[46],"limited":[47],"scalability,":[48],"as":[49],"many":[50],"methods":[51],"rely":[52],"on":[53,118,164,183],"costly":[54],"whole-graph":[55],"operations.":[56],"To":[57,95,127],"address":[58],"them,":[59],"we":[60,100,131],"propose":[61],"SAGAD,":[62],"a":[63,133],"Scalable":[64],"Adaptive":[66,105],"framework":[67],"for":[68,124],"GAD.":[69],"SAGAD":[70,149,168],"precomputes":[71],"multi-hop":[72],"embeddings":[73,113],"applies":[75],"reparameterized":[76],"Chebyshev":[77],"filters":[78],"extract":[80],"low-":[81,110],"high-frequency":[83,144],"information,":[84],"enabling":[85],"efficient":[86],"training":[87],"capturing":[89],"homophilic":[91],"heterophilic":[93],"patterns.":[94],"mitigate":[96],"node-level":[97],"introduce":[101],"an":[102],"Anomaly":[103],"Context-Aware":[104],"Fusion,":[106],"which":[107,138],"adaptively":[108],"fuses":[109],"high-pass":[112],"using":[114],"fusion":[115],"coefficients":[116],"conditioned":[117],"Rayleigh":[119],"Quotient-guided":[120],"anomalous":[121],"subgraph":[122],"structures":[123],"each":[125],"node.":[126],"alleviate":[128],"class-level":[129],"design":[132],"Frequency":[134],"Preference":[135],"Guidance":[136],"Loss,":[137],"encourages":[139],"anomalies":[140],"preserve":[142],"more":[143],"information":[145],"than":[146],"nodes.":[148],"supports":[150],"mini-batch":[151],"training,":[152],"achieves":[153],"linear":[154,171],"time":[155],"space":[157],"complexity,":[158],"drastically":[160],"reduces":[161],"memory":[162],"usage":[163],"large-scale":[165],"graphs.":[166],"Theoretically,":[167],"ensures":[169],"asymptotic":[170],"separability":[172],"between":[173],"abnormal":[176],"under":[178],"mild":[179],"conditions.":[180],"Extensive":[181],"experiments":[182],"10":[184],"benchmarks":[185],"confirm":[186],"SAGAD's":[187],"superior":[188],"accuracy":[189],"scalability":[191],"over":[192],"state-of-the-art":[193],"methods.":[194]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-11T00:00:00"}
