{"id":"https://openalex.org/W7160901190","doi":"https://doi.org/10.48550/arxiv.2605.08765","title":"Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning","display_name":"Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning","publication_year":2026,"publication_date":"2026-05-09","ids":{"openalex":"https://openalex.org/W7160901190","doi":"https://doi.org/10.48550/arxiv.2605.08765"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.08765","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08765","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.2605.08765","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135943475","display_name":"Renjie Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Renjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135965674","display_name":"Jiazhen Du","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Du, Jiazhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135959470","display_name":"Yihua Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yihua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135954996","display_name":"Sijia Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Sijia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.26249998807907104,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.26249998807907104,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.1354999989271164,"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":0.11959999799728394,"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/honesty","display_name":"Honesty","score":0.9659000039100647},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5414999723434448},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5227000117301941},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.5087000131607056},{"id":"https://openalex.org/keywords/mainstream","display_name":"Mainstream","score":0.45329999923706055},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.33809998631477356}],"concepts":[{"id":"https://openalex.org/C2777293324","wikidata":"https://www.wikidata.org/wiki/Q337349","display_name":"Honesty","level":2,"score":0.9659000039100647},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.5690000057220459},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5227000117301941},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.5087000131607056},{"id":"https://openalex.org/C2777617010","wikidata":"https://www.wikidata.org/wiki/Q18957","display_name":"Mainstream","level":2,"score":0.45329999923706055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.444599986076355},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.39969998598098755},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.34209999442100525},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.328900009393692},{"id":"https://openalex.org/C2779267917","wikidata":"https://www.wikidata.org/wiki/Q170028","display_name":"Deception","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.08765","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08765","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.2605.08765","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.08765","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6202040910720825}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unlearning":[0],"in":[1,59,135],"large":[2],"language":[3],"models":[4,172],"(LLMs)":[5],"aims":[6],"to":[7,37,53,93,100,103,153,173],"remove":[8],"harmful":[9],"training":[10],"data":[11,216],"while":[12,89],"preserving":[13,76],"overall":[14],"utility.":[15],"However,":[16],"we":[17,113,162],"find":[18],"that":[19,119,148,168],"existing":[20],"methods":[21,142,151],"often":[22,46],"hallucinate,":[23],"generate":[24],"abnormal":[25],"token":[26],"sequences,":[27],"or":[28],"behave":[29],"inconsistently,":[30],"raising":[31],"safety":[32],"and":[33,79,84,97,132,137,159,217],"trust":[34],"concerns.":[35],"According":[36],"prior":[38],"literature":[39],"on":[40,81,123,209],"LLM":[41],"honesty,":[42,72],"such":[43],"behaviors":[44],"are":[45],"associated":[47],"with":[48],"dishonesty.":[49],"This":[50],"motivates":[51],"us":[52],"investigate":[54],"the":[55,60,91,109,124,182,187,198,201,210],"notion":[56],"of":[57,62,70,111,117,128,194,200],"honesty":[58,80,110,122,208],"context":[61],"model":[63,92],"unlearning.":[64],"We":[65,213],"propose":[66],"a":[67,115,165],"formal":[68],"definition":[69],"unlearning":[71],"which":[73],"includes:":[74],"(1)":[75],"both":[77],"utility":[78],"retained":[82,125,211],"knowledge,":[83],"(2)":[85],"ensuring":[86],"effective":[87],"forgetting":[88],"encouraging":[90],"acknowledge":[94,175],"its":[95],"limitations":[96],"respond":[98],"consistently":[99],"questions":[101],"related":[102],"forgotten":[104,176],"knowledge.":[105,177],"To":[106],"systematically":[107],"evaluate":[108],"unlearning,":[112],"introduce":[114],"suite":[116],"metrics":[118],"cover":[120],"utility,":[121],"set,":[126,184],"effectiveness":[127],"forgetting,":[129],"rejection":[130,189],"rate":[131,190],"refusal":[133],"stability":[134],"Q&amp;A":[136,179],"MCQ":[138],"settings.":[139],"Evaluating":[140],"9":[141],"across":[143],"3":[144],"mainstream":[145],"families":[146],"shows":[147],"all":[149],"current":[150],"fail":[152],"meet":[154],"these":[155],"standards.":[156],"After":[157],"experimental":[158],"theoretical":[160],"analyses,":[161],"present":[163],"ReVa,":[164],"representation-alignment":[166],"procedure":[167],"fine-tunes":[169],"feature-randomized":[170],"unlearned":[171],"better":[174],"On":[178],"tasks":[180],"from":[181],"forget":[183],"ReVa":[185],"achieves":[186],"highest":[188],"after":[191],"two":[192],"rounds":[193],"interaction,":[195],"nearly":[196],"doubling":[197],"performance":[199],"second-best":[202],"method.":[203],"Remarkably,":[204],"It":[205],"also":[206],"improves":[207],"set.":[212],"release":[214],"our":[215],"code":[218],"at":[219],"https://github.com/renjiegu.":[220]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-13T00:00:00"}
