{"id":"https://openalex.org/W4416157139","doi":"https://doi.org/10.48550/arxiv.2511.06073","title":"Stemming Hallucination in Language Models Using a Licensing Oracle","display_name":"Stemming Hallucination in Language Models Using a Licensing Oracle","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416157139","doi":"https://doi.org/10.48550/arxiv.2511.06073"},"language":null,"primary_location":{"id":"pmh:oai:arXiv.org:2511.06073","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.06073","pdf_url":"https://arxiv.org/pdf/2511.06073","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":"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/2511.06073","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120024809","display_name":"Simeon Emanuilov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emanuilov, Simeon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Ackermann, Richard","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ackermann, Richard","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/T10028","display_name":"Topic Modeling","score":0.5562000274658203,"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/T10028","display_name":"Topic Modeling","score":0.5562000274658203,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.10939999669790268,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.06469999998807907,"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/oracle","display_name":"Oracle","score":0.8510000109672546},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4442000091075897},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.4341000020503998},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4056999981403351},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.39480000734329224},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.36250001192092896}],"concepts":[{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.8510000109672546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7587000131607056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48100000619888306},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4442000091075897},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4341000020503998},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38839998841285706},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.36250001192092896},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34290000796318054},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3395000100135803},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3165999948978424},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.29919999837875366},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.2946999967098236},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.27219998836517334},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.25699999928474426}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2511.06073","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.06073","pdf_url":"https://arxiv.org/pdf/2511.06073","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2511.06073","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2511.06073","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2511.06073","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2511.06073","pdf_url":"https://arxiv.org/pdf/2511.06073","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":"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":{"Language":[0],"models":[1],"exhibit":[2],"remarkable":[3],"natural":[4],"language":[5,97],"generation":[6,110,211],"capabilities":[7],"but":[8],"remain":[9],"prone":[10],"to":[11,32,124,198],"hallucinations,":[12],"generating":[13],"factually":[14,74],"incorrect":[15],"information":[16],"despite":[17],"producing":[18],"syntactically":[19],"coherent":[20],"responses.":[21,158],"This":[22,159],"study":[23],"introduces":[24],"the":[25,58,67,81,84,129,167,192,207],"Licensing":[26,59,85,130,168,193],"Oracle,":[27,169],"an":[28],"architectural":[29,163],"solution":[30,175],"designed":[31,197],"stem":[33],"hallucinations":[34,177,200],"in":[35,156,178,201,212],"LMs":[36],"by":[37],"enforcing":[38],"truth":[39],"constraints":[40],"through":[41,87],"formal":[42],"validation":[43,64],"against":[44],"structured":[45,181],"knowledge":[46,182],"graphs.":[47],"Unlike":[48],"statistical":[49,187],"approaches":[50],"that":[51,72,115,147,162,186],"rely":[52],"on":[53],"data":[54],"scaling":[55],"or":[56],"fine-tuning,":[57],"Oracle":[60,86,131,194],"embeds":[61],"a":[62,171,217],"deterministic":[63],"step":[65],"into":[66],"model's":[68],"generative":[69],"process,":[70],"ensuring":[71,146],"only":[73,148],"accurate":[75],"claims":[76,150],"are":[77],"made.":[78],"We":[79],"evaluated":[80],"effectiveness":[82],"of":[83],"experiments":[88],"comparing":[89],"it":[90],"with":[91,153,180],"several":[92],"state-of-the-art":[93],"methods,":[94],"including":[95],"baseline":[96],"model":[98],"generation,":[99],"fine-tuning":[100,104,119],"for":[101,105,176,209],"factual":[102,157],"recall,":[103],"abstention":[106,134],"behavior,":[107],"and":[108,118,139,173],"retrieval-augmented":[109],"(RAG).":[111],"Our":[112],"results":[113],"demonstrate":[114],"although":[116],"RAG":[117],"improve":[120],"performance,":[121],"they":[122],"fail":[123],"eliminate":[125],"hallucinations.":[126],"In":[127],"contrast,":[128],"achieved":[132],"perfect":[133],"precision":[135],"(AP":[136],"=":[137,144],"1.0)":[138],"zero":[140],"false":[141],"answers":[142],"(FAR-NE":[143],"0.0),":[145],"valid":[149],"were":[151],"generated":[152],"89.1%":[154],"accuracy":[155],"work":[160],"shows":[161],"innovations,":[164],"such":[165],"as":[166],"offer":[170],"necessary":[172],"sufficient":[174],"domains":[179],"representations,":[183],"offering":[184],"guarantees":[185],"methods":[188],"cannot":[189],"match.":[190],"Although":[191],"is":[195],"specifically":[196],"address":[199],"fact-based":[202],"domains,":[203],"its":[204],"framework":[205],"lays":[206],"groundwork":[208],"truth-constrained":[210],"future":[213],"AI":[214],"systems,":[215],"providing":[216],"new":[218],"path":[219],"toward":[220],"reliable,":[221],"epistemically":[222],"grounded":[223],"models.":[224]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2025-11-12T00:00:00"}
