{"id":"https://openalex.org/W7162551610","doi":"https://doi.org/10.48550/arxiv.2605.27016","title":"Evaluating the Relevance of Uncertainty Estimators for LLM Hallucination","display_name":"Evaluating the Relevance of Uncertainty Estimators for LLM Hallucination","publication_year":2026,"publication_date":"2026-05-26","ids":{"openalex":"https://openalex.org/W7162551610","doi":"https://doi.org/10.48550/arxiv.2605.27016"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.27016","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27016","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":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.2605.27016","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137102057","display_name":"Yedidia Agnimo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Agnimo, Yedidia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059202725","display_name":"Anna Korba","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Korba, Anna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016976205","display_name":"Annabelle Blangero","orcid":"https://orcid.org/0000-0002-5799-5665"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Blangero, Annabelle","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060566931","display_name":"Nicolas Chesneau","orcid":"https://orcid.org/0000-0002-8313-5829"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chesneau, Nicolas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5049440980","display_name":"Karteek Alahari","orcid":"https://orcid.org/0000-0002-1838-5936"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alahari, Karteek","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.2529999911785126,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.2529999911785126,"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/T10028","display_name":"Topic Modeling","score":0.1225999966263771,"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":0.08079999685287476,"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/estimator","display_name":"Estimator","score":0.7132999897003174},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5781999826431274},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5289000272750854},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.41019999980926514},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.37380000948905945},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3294999897480011}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7132999897003174},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5781999826431274},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5289000272750854},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.49799999594688416},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.41339999437332153},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4047999978065491},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3991999924182892},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.37380000948905945},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3287000060081482},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.32170000672340393},{"id":"https://openalex.org/C13200473","wikidata":"https://www.wikidata.org/wiki/Q2747831","display_name":"Reflexivity","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2935999929904938},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2913999855518341},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27079999446868896},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.27016","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27016","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":"doi:10.48550/arxiv.2605.27016","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27016","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":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":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"are":[4,35],"prone":[5],"to":[6,30,80,122],"hallucinations,":[7],"i.e.,":[8],"statements":[9],"unsupported":[10],"by":[11],"the":[12,45,61,136,146,150,157],"input":[13,114],"or":[14],"training":[15,123],"data,":[16],"hindering":[17],"reliable":[18],"deployment.":[19],"In":[20],"parallel,":[21],"numerous":[22],"uncertainty":[23,48,64,91,160],"estimation":[24],"(UE)":[25],"methods":[26],"have":[27],"been":[28],"proposed":[29],"quantify":[31],"model":[32,42],"confidence":[33],"and":[34,49,66,79,96,99,116,131,141,149,167],"often":[36,142],"implicitly":[37],"treated":[38],"as":[39,161],"proxies":[40],"for":[41],"failure.":[43],"However,":[44],"relationship":[46],"between":[47,63],"hallucinations":[50,67,111,118],"remains":[51],"insufficiently":[52],"characterized.":[53],"We":[54,85,133],"present":[55],"a":[56,87,162],"systematic":[57],"empirical":[58],"study":[59],"of":[60,90,113,159,165],"association":[62,137],"estimators":[65],"in":[68],"LLMs.":[69],"Rather":[70],"than":[71],"assuming":[72],"this":[73],"association,":[74],"we":[75],"evaluate":[76],"directly":[77],"when":[78,169],"what":[81],"extent":[82],"it":[83,170],"holds.":[84],"consider":[86],"diverse":[88],"set":[89],"estimators,":[92,98],"including":[93,129],"information-theoretic,":[94],"sampling-based,":[95],"reflexive":[97],"examine":[100],"their":[101],"behavior":[102],"across":[103],"hallucination":[104,147,166],"settings.":[105],"Our":[106],"experiments":[107],"cover":[108],"both":[109],"intrinsic":[110],"(violations":[112],"faithfulness)":[115],"extrinsic":[117],"(unsupported":[119],"claims":[120],"relative":[121],"data),":[124],"using":[125],"four":[126],"complementary":[127],"benchmarks,":[128],"RAGTruth":[130],"HalluLens.":[132],"find":[134],"that":[135],"is":[138],"highly":[139],"variable":[140],"weak,":[143],"depending":[144],"on":[145],"type":[148],"LLM":[151],"under":[152],"evaluation.":[153],"These":[154],"results":[155],"challenge":[156],"use":[158],"direct":[163],"signal":[164],"clarify":[168],"provides":[171],"actionable":[172],"information.":[173]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-28T00:00:00"}