{"id":"https://openalex.org/W7162465196","doi":"https://doi.org/10.48550/arxiv.2605.26068","title":"Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark","display_name":"Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark","publication_year":2026,"publication_date":"2026-05-25","ids":{"openalex":"https://openalex.org/W7162465196","doi":"https://doi.org/10.48550/arxiv.2605.26068"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.26068","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26068","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"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":"https://doi.org/10.48550/arxiv.2605.26068","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072631894","display_name":"Xu Yao","orcid":"https://orcid.org/0009-0002-8936-3213"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137006799","display_name":"Siyuan Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Siyuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077903873","display_name":"WU ZhenBo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zhenbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018277720","display_name":"Chaochuan Hou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hou, Chaochuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137071177","display_name":"Shuang Liang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang, Shuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137041385","display_name":"Shiping Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shiping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137030048","display_name":"Hailiang Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Hailiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003652858","display_name":"Songqiao Han","orcid":"https://orcid.org/0000-0002-2896-0607"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Songqiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137070063","display_name":"Minqi Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Minqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.7609999775886536,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.7609999775886536,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.1768999993801117,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.014299999922513962,"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/benchmarking","display_name":"Benchmarking","score":0.8694999814033508},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.8299999833106995},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6596999764442444},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.44749999046325684},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.44369998574256897},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4399999976158142},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4174000024795532},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.335099995136261}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8694999814033508},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8299999833106995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6626999974250793},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6596999764442444},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5874999761581421},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.474700003862381},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.44749999046325684},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.44369998574256897},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4399999976158142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43299999833106995},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4174000024795532},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.26660001277923584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.26068","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26068","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.26068","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.26068","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Weakly":[0],"supervised":[1,49],"anomaly":[2],"detection":[3],"(WSAD)":[4],"has":[5],"developed":[6],"in":[7,122,142],"three":[8],"primary":[9],"directions:":[10],"incomplete,":[11],"inexact,":[12],"and":[13,80,134,180],"inaccurate":[14],"supervision.":[15],"However,":[16],"these":[17,105],"directions":[18],"remain":[19],"isolated,":[20],"lacking":[21],"a":[22],"unified":[23],"framework":[24],"to":[25,58,67,157,165,182],"assess":[26],"whether":[27],"they":[28],"address":[29],"unique":[30],"challenges":[31],"or":[32,141],"share":[33],"fundamental":[34],"mechanisms.":[35],"This":[36],"paper":[37],"introduces":[38],"WSADBench,":[39],"the":[40,83,110],"first":[41],"benchmark":[42,177],"that":[43],"unifies":[44],"evaluation":[45],"across":[46,71,151],"distinct":[47],"weakly":[48],"scenarios,":[50,108],"benchmarking":[51],"diverse":[52],"approaches":[53],"from":[54],"specialized":[55],"WSAD":[56,118,185],"methods":[57,137],"advanced":[59],"tabular":[60,131],"foundation":[61,132],"models.":[62],"WSADBench":[63,94,173],"establishes":[64],"standardized":[65],"protocols":[66],"evaluate":[68],"36":[69],"algorithms":[70,119],"4":[72],"modalities":[73],"by":[74,130],"systematically":[75],"varying":[76],"label":[77,158,169],"quantity,":[78],"granularity,":[79],"quality,":[81],"revealing":[82],"performance":[84],"boundaries":[85],"of":[86,112,168],"various":[87],"methods.":[88],"Based":[89],"on":[90],"over":[91],"700K":[92],"experiments,":[93],"reveals":[95],"four":[96],"critical":[97],"insights:":[98],"(i)":[99],"Strong":[100],"intrinsic":[101],"correlations":[102],"exist":[103],"between":[104],"weak":[106],"supervision":[107,139],"challenging":[109],"isolation":[111],"current":[113],"research":[114],"directions.":[115],"(ii)":[116],"Specialized":[117],"excel":[120],"only":[121],"extreme":[123],"label-scarcity":[124],"regimes":[125],"but":[126],"are":[127],"quickly":[128],"dominated":[129],"models":[133],"general":[135],"classification":[136],"as":[138,174],"increases":[140],"OOD":[143],"scenarios.":[144],"(iii)":[145],"Unlabeled":[146],"data":[147],"shows":[148],"inconsistent":[149],"utility":[150],"settings,":[152],"with":[153,178],"marginal":[154],"gains":[155],"compared":[156],"refinement.":[159],"(iv)":[160],"Models":[161],"exhibit":[162],"asymmetric":[163],"sensitivity":[164],"different":[166],"types":[167],"noise.":[170],"We":[171],"release":[172],"an":[175],"open-source":[176],"code":[179],"datasets":[181],"facilitate":[183],"future":[184],"research:":[186],"https://github.com/SUFE-AILAB/WSADBench.":[187]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-27T00:00:00"}
