{"id":"https://openalex.org/W7128375967","doi":"https://doi.org/10.48550/arxiv.2602.06859","title":"Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts","display_name":"Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts","publication_year":2026,"publication_date":"2026-02-06","ids":{"openalex":"https://openalex.org/W7128375967","doi":"https://doi.org/10.48550/arxiv.2602.06859"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2602.06859","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2602.06859","pdf_url":"https://arxiv.org/pdf/2602.06859","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2602.06859","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125377964","display_name":"Xinyu Zhao","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Xinyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018132697","display_name":"Qingyun Sun","orcid":"https://orcid.org/0000-0003-1930-3848","observed_orcids":["https://orcid.org/0000-0003-1930-3848"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Qingyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125401499","display_name":"Jiayi Luo","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Jiayi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044043709","display_name":"Xingcheng Fu","orcid":"https://orcid.org/0000-0002-4643-8126","observed_orcids":["https://orcid.org/0000-0002-4643-8126"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Xingcheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125400993","display_name":"Jianxin Li","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jianxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.6509000062942505,"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":0.6509000062942505,"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":0.3345000147819519,"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":0.00570000009611249,"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/graph-anomaly-detection","display_name":"graph anomaly detection","score":0.996999979019165},{"id":"https://openalex.org/keywords/zero-shot-generalization","display_name":"zero-shot generalization","score":0.8930000066757202},{"id":"https://openalex.org/keywords/riemannian-geometry","display_name":"Riemannian geometry","score":0.8519999980926514},{"id":"https://openalex.org/keywords/domain-generalization","display_name":"domain generalization","score":0.7799999713897705},{"id":"https://openalex.org/keywords/network-embedding","display_name":"graph embedding","score":0.39800000190734863}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6251000165939331},{"id":"https://openalex.org/C195065555","wikidata":"https://www.wikidata.org/wiki/Q214881","display_name":"Curvature","level":2,"score":0.5619000196456909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49900001287460327},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49889999628067017},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39730000495910645},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38350000977516174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.34619998931884766},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3418999910354614},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C169391604","wikidata":"https://www.wikidata.org/wiki/Q7604402","display_name":"Statistical manifold","level":5,"score":0.2831000089645386},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2736000120639801},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2612000107765198},{"id":"https://openalex.org/C2779593128","wikidata":"https://www.wikidata.org/wiki/Q632814","display_name":"Riemannian manifold","level":2,"score":0.2599000036716461}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2602.06859","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2602.06859","pdf_url":"https://arxiv.org/pdf/2602.06859","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2602.06859","doi":"https://doi.org/10.48550/arxiv.2602.06859","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.06859","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2602.06859","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2602.06859","pdf_url":"https://arxiv.org/pdf/2602.06859","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"score":0.43880757689476013,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Graph":[0,106],"Anomaly":[1,107],"Detection":[2,108],"(GAD)":[3],"aims":[4],"to":[5,20,23,117,180,198],"identify":[6],"irregular":[7],"patterns":[8],"in":[9,125,145,213],"graph":[10,25,94],"data,":[11],"and":[12,62],"recent":[13],"works":[14],"have":[15],"explored":[16],"zero-shot":[17,29,104,215],"generalist":[18,223],"GAD":[19,30,224],"enable":[21],"generalization":[22,183],"unseen":[24],"datasets.":[26],"However,":[27],"existing":[28],"methods":[31],"largely":[32],"ignore":[33],"intrinsic":[34],"geometric":[35,60],"differences":[36],"across":[37],"diverse":[38],"anomaly":[39,52,95,121],"patterns,":[40,96,186],"substantially":[41],"limiting":[42],"their":[43],"cross-domain":[44],"generalization.":[45],"In":[46],"this":[47],"work,":[48],"we":[49,97,159,187],"reveal":[50],"that":[51,63,86,119,167,193,218],"detectability":[53],"is":[54,123,131],"highly":[55],"dependent":[56],"on":[57,204,208],"the":[58,77,84,126,155,199,214],"underlying":[59],"properties":[61],"embedding":[64],"graphs":[65],"from":[66],"different":[67],"domains":[68],"into":[69],"a":[70,87,100,110,136,146,189],"single":[71,88],"static":[72],"curvature":[73,89,148],"space":[74,90,128],"can":[75],"distort":[76],"structural":[78],"signatures":[79],"of":[80,112,138],"anomalies.":[81,210],"To":[82,150],"address":[83],"challenge":[85],"cannot":[91],"capture":[92],"geometry-dependent":[93],"propose":[98],"GAD-MoRE,":[99],"novel":[101],"framework":[102],"for":[103,154],"Generalizable":[105],"with":[109,171],"Mixture":[111],"Riemannian":[113,127,140,157],"Experts":[114],"architecture.":[115],"Specifically,":[116],"ensure":[118],"each":[120,143,196],"pattern":[122],"modeled":[124],"where":[129],"it":[130],"most":[132,200],"detectable,":[133],"GAD-MoRE":[134,219],"employs":[135],"set":[137],"specialized":[139],"expert":[141,202],"networks,":[142],"operating":[144],"distinct":[147],"space.":[149],"construct":[151],"topology-aware":[152],"inputs":[153],"subsequent":[156],"experts,":[158],"introduce":[160],"an":[161],"anomaly-aware":[162],"multi-curvature":[163],"feature":[164,173,177],"alignment":[165],"module":[166],"combines":[168],"dimensionality":[169],"reduction":[170],"Laplacian":[172],"selection":[174],"over":[175],"parallel":[176],"branches.":[178],"Finally,":[179],"facilitate":[181],"better":[182],"beyond":[184],"seen":[185],"design":[188],"memory-based":[190],"dynamic":[191],"router":[192],"adaptively":[194],"assigns":[195],"input":[197],"compatible":[201],"based":[203],"historical":[205],"reconstruction":[206],"performance":[207],"similar":[209],"Extensive":[211],"experiments":[212],"setting":[216],"demonstrate":[217],"significantly":[220],"outperforms":[221],"state-of-the-art":[222],"baselines.":[225]},"counts_by_year":[],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2026-02-10T00:00:00"}