{"id":"https://openalex.org/W7163033548","doi":"https://doi.org/10.48550/arxiv.2605.30919","title":"De-attribute to Forget for LLM Unlearning","display_name":"De-attribute to Forget for LLM Unlearning","publication_year":2026,"publication_date":"2026-05-29","ids":{"openalex":"https://openalex.org/W7163033548","doi":"https://doi.org/10.48550/arxiv.2605.30919"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.30919","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30919","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.30919","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137551595","display_name":"Xinyang Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Xinyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137560908","display_name":"Jiabao Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Jiabao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085515319","display_name":"Rachael Hwee Ling Sim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sim, Rachael Hwee Ling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137558442","display_name":"See-Kiong Ng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ng, See-Kiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137547206","display_name":"Anthony Kum Hoe Tung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tung, Anthony Kum Hoe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137560548","display_name":"Bryan Kian Hsiang Low","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Low, Bryan Kian Hsiang","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":0.3206999897956848,"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":0.3206999897956848,"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":0.17299999296665192,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.05420000106096268,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/attribution","display_name":"Attribution","score":0.5623000264167786},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.3833000063896179},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.37439998984336853},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.35269999504089355},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.3479999899864197}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6624000072479248},{"id":"https://openalex.org/C143299363","wikidata":"https://www.wikidata.org/wiki/Q900584","display_name":"Attribution","level":2,"score":0.5623000264167786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5383999943733215},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.37439998984336853},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3479999899864197},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3206999897956848},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.26649999618530273},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.30919","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30919","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":"doi:10.48550/arxiv.2605.30919","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.30919","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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","score":0.5771690011024475,"display_name":"No poverty"}],"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],"rapid":[1],"development":[2],"of":[3,14,74,109,130],"large":[4],"language":[5],"models":[6],"(LLMs)":[7],"has":[8,20],"raised":[9],"concerns":[10],"on":[11,35,44,90],"the":[12,42,45,66,84,102,106,116],"use":[13],"inappropriate":[15],"data":[16,77,91,118],"for":[17,69],"training,":[18],"which":[19],"led":[21],"to":[22,100,115],"a":[23],"growing":[24],"interest":[25],"in":[26],"LLM":[27,31,70,86,103,124],"unlearning.":[28],"Many":[29],"existing":[30,136],"unlearning":[32,71,87,141],"approaches":[33],"rely":[34],"optimizing":[36],"prediction":[37],"loss(es),":[38],"such":[39],"as":[40,72,126],"maximizing":[41],"loss":[43],"forget":[46,117,144],"set,":[47],"but":[48],"often":[49],"face":[50],"critical":[51],"issues":[52],"like":[53],"over-forgetting":[54],"and":[55,146],"poor":[56],"model":[57,147],"utility.":[58],"To":[59],"address":[60],"them,":[61],"this":[62],"paper":[63],"novelly":[64],"frames":[65],"optimization":[67],"objective":[68],"one":[73],"zeroing":[75],"out":[76],"attribution":[78,92,107,131],"instead.":[79],"In":[80],"particular,":[81],"we":[82],"propose":[83],"first":[85],"framework":[88],"based":[89],"rewards":[93],"called":[94],"DareU":[95,134],"that":[96,133],"performs":[97],"reinforcement":[98],"learning":[99],"update":[101],"by":[104,138],"reducing":[105],"score":[108],"its":[110],"generated":[111],"responses":[112],"(i.e.,":[113],"de-attributing)":[114],"owners.":[119],"Empirical":[120],"evaluation":[121],"using":[122],"an":[123,127],"classifier":[125],"efficient":[128],"approximation":[129],"shows":[132],"outperforms":[135],"baselines":[137],"achieving":[139],"effective":[140],"while":[142],"balancing":[143],"quality":[145],"utility":[148],"well.":[149]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-02T00:00:00"}
