{"id":"https://openalex.org/W4417462425","doi":"https://doi.org/10.48550/arxiv.2512.13704","title":"Adjudicator: Correcting Noisy Labels with a KG-Informed Council of LLM Agents","display_name":"Adjudicator: Correcting Noisy Labels with a KG-Informed Council of LLM Agents","publication_year":2025,"publication_date":"2025-12-05","ids":{"openalex":"https://openalex.org/W4417462425","doi":"https://doi.org/10.48550/arxiv.2512.13704"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2512.13704","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.13704","pdf_url":"https://arxiv.org/pdf/2512.13704","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2512.13704","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120844795","display_name":"Doohee You","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"You, Doohee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5120844796","display_name":"Sundeep Paul","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paul, Sundeep","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.8467000126838684,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.8467000126838684,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.03669999912381172,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.011500000022351742,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5012000203132629},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4643999934196472},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.45840001106262207},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.45590001344680786},{"id":"https://openalex.org/keywords/production","display_name":"Production (economics)","score":0.4115999937057495},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.3959999978542328},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.38499999046325684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7261999845504761},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5422999858856201},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.484499990940094},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4643999934196472},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45840001106262207},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.45590001344680786},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39480000734329224},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.38499999046325684},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.3797999918460846},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2962999939918518},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2512.13704","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.13704","pdf_url":"https://arxiv.org/pdf/2512.13704","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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.2512.13704","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2512.13704","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:oai:arXiv.org:2512.13704","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2512.13704","pdf_url":"https://arxiv.org/pdf/2512.13704","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"performance":[1,25],"of":[2,13,43,81,109,163],"production":[3,55],"machine":[4],"learning":[5],"systems":[6],"is":[7,137],"fundamentally":[8],"limited":[9],"by":[10,143],"the":[11,38,110,150],"quality":[12],"their":[14],"training":[15],"data.":[16],"In":[17],"high-stakes":[18],"industrial":[19,195],"applications,":[20],"noisy":[21],"labels":[22],"can":[23],"degrade":[24],"and":[26,46,50,94,127,175],"erode":[27],"user":[28],"trust.":[29],"This":[30,75,170],"paper":[31],"presents":[32],"Adjudicator,":[33],"a":[34,61,66,79,83,97,105,117,122,128,140,144,161,173,185],"system":[35,103,177],"that":[36,148,165],"addresses":[37],"critical":[39],"data":[40,181],"mining":[41],"challenge":[42],"automatically":[44],"identifying":[45],"correcting":[47],"label":[48],"noise":[49],"has":[51],"been":[52],"validated":[53],"for":[54,178,188],"deployment.":[56],"Adjudicator":[57],"models":[58],"this":[59,136],"as":[60,184],"neuro-symbolic":[62],"task,":[63],"first":[64],"constructing":[65],"dynamic":[67],"Knowledge":[68],"Graph":[69],"(KG)":[70],"to":[71,139,152,168],"unify":[72],"item":[73],"context.":[74],"KG":[76,151],"then":[77],"informs":[78],"\"Council":[80],"Agents,\"":[82],"novel":[84,145],"multi-agent":[85],"Large":[86],"Language":[87],"Model":[88],"architecture":[89],"where":[90],"specialized":[91],"agents":[92],"debate":[93],"vote":[95],"on":[96,104],"label's":[98],"validity.":[99],"We":[100],"validate":[101],"our":[102],"1,000-item":[106],"balanced":[107],"subset":[108],"AlleNoise":[111],"benchmark.":[112],"Our":[113,133],"KG-informed":[114],"model":[115],"achieves":[116],"0.99":[118],"F1-score,":[119],"significantly":[120],"outperforming":[121],"single-LLM":[123],"baseline":[124],"(0.48":[125],"F1)":[126],"non-KG":[129],"council":[130],"(0.59":[131],"F1).":[132],"analysis":[134],"reveals":[135],"due":[138],"Precision,":[141],"achieved":[142],"override":[146],"logic":[147],"uses":[149],"perfectly":[153],"identify":[154],"complex,":[155],"structural":[156],"errors":[157,164],"(complete":[158],"Recall)":[159],"--":[160],"class":[162],"baselines":[166],"fail":[167],"find.":[169],"result":[171],"demonstrates":[172],"robust":[174],"explainable":[176],"automated,":[179],"high-precision":[180],"verification,":[182],"serving":[183],"vital":[186],"proof-of-concept":[187],"generating":[189],"golden":[190],"datasets":[191],"in":[192],"strictly":[193],"governed":[194],"environments.":[196]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-18T00:00:00"}
