{"id":"https://openalex.org/W4415035389","doi":"https://doi.org/10.18653/v1/2026.findings-acl.2085","title":"DUSK: Do Not Unlearn Shared Knowledge","display_name":"DUSK: Do Not Unlearn Shared Knowledge","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4415035389","doi":"https://doi.org/10.18653/v1/2026.findings-acl.2085"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.2085","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.2085","pdf_url":"https://aclanthology.org/2026.findings-acl.2085.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.2085.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119938073","display_name":"Wonje Jeung","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wonje Jeung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007040475","display_name":"Sangyeon Yoon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sangyeon Yoon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119938074","display_name":"Hyesoo Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hyesoo Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032816630","display_name":"Soeun Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soeun Kim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053165370","display_name":"Seungju Han","orcid":"https://orcid.org/0000-0001-7293-1419"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seungju Han","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101881857","display_name":"Youngjae Yu","orcid":"https://orcid.org/0000-0002-5867-0782"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Youngjae Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5049196468","display_name":"Albert No","orcid":"https://orcid.org/0000-0002-6346-4182"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Albert No","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":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01159351,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"42013","last_page":"42031"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.39879998564720154,"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":0.39879998564720154,"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/T11719","display_name":"Data Quality and Management","score":0.0544000007212162,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.040699999779462814,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/set","display_name":"Set (abstract data type)","score":0.6000000238418579},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5636000037193298},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5151000022888184},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.4332999885082245},{"id":"https://openalex.org/keywords/raising","display_name":"Raising (metalworking)","score":0.4311000108718872}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7182000279426575},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6000000238418579},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5636000037193298},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5151000022888184},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C2780589192","wikidata":"https://www.wikidata.org/wiki/Q7285140","display_name":"Raising (metalworking)","level":2,"score":0.4311000108718872},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.41530001163482666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3889999985694885},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.25679999589920044}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.2085","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.2085","pdf_url":"https://aclanthology.org/2026.findings-acl.2085.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2505.15209","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2505.15209","pdf_url":"https://arxiv.org/pdf/2505.15209","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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2505.15209","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2505.15209","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,"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:10.18653/v1/2026.findings-acl.2085","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.2085","pdf_url":"https://aclanthology.org/2026.findings-acl.2085.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: ACL 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2257911995","display_name":null,"funder_award_id":"RS-2020-II201361","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G2759505043","display_name":null,"funder_award_id":"RS-202400457882","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G3182541678","display_name":null,"funder_award_id":"RS-2020-II201361","funder_id":"https://openalex.org/F4320321314","funder_display_name":"Yonsei University"},{"id":"https://openalex.org/G3212097187","display_name":null,"funder_award_id":"RS-2020-II201361","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G5704809196","display_name":null,"funder_award_id":"RS-2024-00457882","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G8899733881","display_name":null,"funder_award_id":"RS-2020-II201361","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321314","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415035389.pdf","grobid_xml":"https://content.openalex.org/works/W4415035389.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Machine":[0],"unlearning":[1,63,138],"aims":[2],"to":[3,80,106,121],"remove":[4],"\"forget\"":[5],"data":[6],"while":[7,47],"preserving":[8],"knowledge":[9,44,66,75],"from":[10,31,109],"the":[11,20,37,59],"\"retain\"":[12],"data,":[13],"yet":[14],"a":[15,32,127],"fundamental":[16],"question":[17],"arises":[18],"when":[19],"two":[21],"share":[22],"content.By":[23],"definition,":[24],"an":[25],"unlearned":[26],"model":[27,33],"should":[28,116],"be":[29,117],"indistinguishable":[30],"retrained":[34],"solely":[35],"on":[36],"retain":[38],"set,":[39],"which":[40],"implies":[41],"that":[42,96,115],"shared":[43,72,89,108],"must":[45],"remain":[46],"only":[48],"forget-specific":[49,85],"content":[50],"is":[51,100],"removed.To":[52],"evaluate":[53],"this":[54],"requirement,":[55],"we":[56,94],"introduce":[57],"DUSK,":[58],"first":[60],"benchmark":[61],"for":[62,131],"under":[64],"realistic":[65],"overlap.DUSK":[67],"constructs":[68],"documents":[69],"containing":[70],"both":[71],"and":[73,76,135],"unique":[74,110],"defines":[77],"seven":[78],"metrics":[79],"test":[81],"whether":[82],"methods":[83,104],"erase":[84],"expressions":[86],"without":[87],"discarding":[88],"facts.Evaluating":[90],"nine":[91],"recent":[92],"approaches,":[93],"find":[95],"although":[97],"surface":[98],"text":[99],"often":[101],"removed,":[102],"current":[103],"struggle":[105],"distinguish":[107],"knowledge,":[111],"either":[112],"erasing":[113],"information":[114],"retained":[118],"or":[119],"failing":[120],"fully":[122],"forget":[123],"target":[124],"content.DUSK":[125],"provides":[126],"controlled,":[128],"reproducible":[129],"testbed":[130],"diagnosing":[132],"these":[133],"failures":[134],"guiding":[136],"precise":[137],"algorithms.":[139]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}