{"id":"https://openalex.org/W7225201950","doi":"https://doi.org/10.48550/arxiv.2611.02620","title":"Adaptive Localization of Knowledge Negation for Continual LLM Unlearning","display_name":"Adaptive Localization of Knowledge Negation for Continual LLM Unlearning","publication_year":2026,"publication_date":"2026-11-02","ids":{"openalex":"https://openalex.org/W7225201950","doi":"https://doi.org/10.48550/arxiv.2611.02620"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2611.02620","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2611.02620","pdf_url":"https://arxiv.org/pdf/2611.02620","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2611.02620","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023291127","display_name":"Abudukelimu Wuerkaixi","orcid":"https://orcid.org/0000-0002-5609-606X","observed_orcids":["https://orcid.org/0000-0002-5609-606X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wuerkaixi, Abudukelimu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160522579","display_name":"Qizhou Wang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Qizhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160416791","display_name":"Sen Cui","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cui, Sen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160413763","display_name":"Wutong Xu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Wutong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160494778","display_name":"Bo Han","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Bo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077897263","display_name":"Gang Niu","orcid":"https://orcid.org/0000-0002-7353-5079","observed_orcids":["https://orcid.org/0000-0002-7353-5079"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Niu, Gang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072744508","display_name":"Masashi Sugiyama","orcid":"https://orcid.org/0000-0001-6658-6743","observed_orcids":["https://orcid.org/0000-0001-6658-6743"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sugiyama, Masashi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5160465057","display_name":"Changshui Zhang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Changshui","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":true,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9833999872207642,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9833999872207642,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.00570000009611249,"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":0.00279999990016222,"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/llm-unlearning","display_name":"LLM unlearning","score":0.902999997138977},{"id":"https://openalex.org/keywords/knowledge-localization","display_name":"knowledge localization","score":0.5360000133514404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.695900022983551},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6607999801635742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5464000105857849},{"id":"https://openalex.org/C2185349","wikidata":"https://www.wikidata.org/wiki/Q190558","display_name":"Negation","level":2,"score":0.5076000094413757},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C2777220311","wikidata":"https://www.wikidata.org/wiki/Q6423340","display_name":"Knowledge acquisition","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2542000114917755}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2611.02620","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2611.02620","pdf_url":"https://arxiv.org/pdf/2611.02620","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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.2611.02620","doi":"https://doi.org/10.48550/arxiv.2611.02620","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2611.02620","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2611.02620","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2611.02620","pdf_url":"https://arxiv.org/pdf/2611.02620","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322832","display_name":"University of Tokyo","ror":"https://ror.org/057zh3y96"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225201950.pdf","grobid_xml":"https://content.openalex.org/works/W7225201950.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7224792724","https://openalex.org/W4400703295","https://openalex.org/W7131384311","https://openalex.org/W7126159022","https://openalex.org/W7127624786","https://openalex.org/W4417409358","https://openalex.org/W7166808545","https://openalex.org/W7162261128","https://openalex.org/W7197020854","https://openalex.org/W7154704313"],"abstract_inverted_index":{"With":[0],"the":[1,39,85,96],"growing":[2],"deployment":[3],"of":[4,41,109],"large":[5],"language":[6],"models":[7],"(LLMs)":[8],"across":[9,131],"diverse":[10],"domains,":[11],"concerns":[12],"regarding":[13],"their":[14],"safety":[15],"have":[16],"grown":[17],"substantially.":[18],"LLM":[19,68,134],"unlearning":[20,53,123,135,147,154],"has":[21],"emerged":[22],"as":[23],"a":[24,102],"pivotal":[25],"approach":[26,140],"to":[27,57,73,84,116],"removing":[28],"harmful":[29],"or":[30],"unlawful":[31],"content":[32],"while":[33,66],"maintaining":[34],"utility.":[35],"Despite":[36],"increasing":[37],"interest,":[38],"challenges":[40],"continual":[42,153],"unlearning,":[43],"which":[44,112],"is":[45,71],"common":[46],"in":[47,76,145],"real-world":[48],"scenarios,":[49],"remain":[50],"underexplored.":[51],"Successive":[52],"tasks":[54],"often":[55],"lead":[56],"intensified":[58],"utility":[59,150],"degradation.":[60],"To":[61],"effectively":[62],"unlearn":[63],"targeted":[64],"knowledge":[65,91],"preserving":[67],"utility,":[69],"it":[70],"essential":[72],"minimize":[74],"changes":[75],"model":[77],"parameters":[78],"by":[79],"selectively":[80],"updating":[81],"those":[82],"linked":[83],"target":[86],"knowledge,":[87],"thereby":[88],"ensuring":[89],"other":[90],"remains":[92],"unaffected.":[93],"Building":[94],"on":[95,126],"task":[97],"vector":[98],"framework,":[99],"we":[100],"propose":[101],"new":[103],"method":[104],"named":[105],"ALKN":[106],"(Adaptive":[107],"Localization":[108],"Knowledge":[110],"Negation),":[111],"uses":[113],"dynamic":[114],"masking":[115],"sparsify":[117],"training":[118],"gradients":[119],"and":[120,149],"adaptively":[121],"adjusts":[122],"intensity":[124],"based":[125],"inter-task":[127],"relationships.":[128],"Comprehensive":[129],"experiments":[130],"three":[132],"well-established":[133],"datasets":[136],"demonstrate":[137],"that":[138],"our":[139],"consistently":[141],"outperforms":[142],"baseline":[143],"methods":[144],"both":[146],"effectiveness":[148],"retention":[151],"under":[152],"settings.":[155]},"counts_by_year":[],"updated_date":"2026-11-06T12:05:46.655746","created_date":"2026-11-04T00:00:00"}