{"id":"https://openalex.org/W7160667239","doi":"https://doi.org/10.48550/arxiv.2605.05871","title":"Retain-Neutral Surrogates for Min-Max Unlearning","display_name":"Retain-Neutral Surrogates for Min-Max Unlearning","publication_year":2026,"publication_date":"2026-05-07","ids":{"openalex":"https://openalex.org/W7160667239","doi":"https://doi.org/10.48550/arxiv.2605.05871"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.05871","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05871","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.05871","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135717208","display_name":"Junhao Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Junhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135671749","display_name":"Dohun Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Dohun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135727872","display_name":"Dowon Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Dowon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135688986","display_name":"Sung Il Choi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Sung Il","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135711620","display_name":"Chengjun Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Chengjun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101793547","display_name":"Juhyun Park","orcid":"https://orcid.org/0000-0001-7112-6493"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Juhyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135693983","display_name":"Changhee Joo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joo, Changhee","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/T10036","display_name":"Advanced Neural Network Applications","score":0.2734000086784363,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.2734000086784363,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.24140000343322754,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.10719999670982361,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/surrogate-model","display_name":"Surrogate model","score":0.48010000586509705},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.47119998931884766},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4383000135421753},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.37040001153945923},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.29319998621940613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5184999704360962},{"id":"https://openalex.org/C131675550","wikidata":"https://www.wikidata.org/wiki/Q7646884","display_name":"Surrogate model","level":2,"score":0.48010000586509705},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.47119998931884766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46149998903274536},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4383000135421753},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C142806159","wikidata":"https://www.wikidata.org/wiki/Q7646876","display_name":"Surrogate data","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27790001034736633},{"id":"https://openalex.org/C61445026","wikidata":"https://www.wikidata.org/wiki/Q217608","display_name":"Fixed point","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26109999418258667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2590999901294708},{"id":"https://openalex.org/C2987804222","wikidata":"https://www.wikidata.org/wiki/Q5376582","display_name":"End point","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.05871","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05871","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.05871","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.05871","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":"Preprint"},"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":{"Machine":[0],"unlearning":[1,19],"seeks":[2],"to":[3,60,86,137],"remove":[4],"the":[5,15,31,36,41,76,110,145,160],"influence":[6],"of":[7],"designated":[8],"training":[9],"data":[10],"while":[11,174],"preserving":[12],"performance":[13],"on":[14,121],"remaining":[16,175],"data.":[17],"Approximate":[18],"can":[20,58],"be":[21],"viewed":[22],"as":[23],"a":[24,61,92,98,102,117,125],"local":[25,33],"editing":[26],"problem;":[27],"in":[28,128,171],"min-max":[29,139],"unlearning,":[30],"key":[32],"object":[34],"is":[35,44],"surrogate":[37,62,78,133],"point":[38,63],"at":[39],"which":[40,74,129],"retain":[42,49,66,89,122,134],"objective":[43],"evaluated.":[45],"When":[46],"forget":[47,83],"and":[48,107,141,153],"gradients":[50,147],"are":[51,148],"strongly":[52],"aligned,":[53],"an":[54],"unconstrained":[55],"forget-maximizing":[56],"perturbation":[57,94],"move":[59],"that":[64],"increases":[65],"loss.":[67],"We":[68],"propose":[69],"Retain-Orthogonal":[70],"Surrogate":[71],"Unlearning":[72],"(ROSU),":[73],"constrains":[75],"inner":[77],"construction":[79],"by":[80],"maximizing":[81],"first-order":[82,88],"gain":[84],"subject":[85],"zero":[87],"change":[90],"under":[91],"fixed":[93],"budget.":[95],"This":[96],"yields":[97],"closed-form":[99],"retain-orthogonal":[100],"perturbation,":[101],"lightweight":[103],"transported":[104],"outer":[105],"update,":[106],"amplification":[108],"along":[109],"retain-neutral":[111],"direction.":[112],"Our":[113],"analysis":[114],"establishes":[115],"(i)":[116],"curvature-controlled":[118],"second-order":[119],"bound":[120],"damage,":[123],"(ii)":[124],"positive-alignment":[126],"regime":[127],"ROSU":[130,166],"strictly":[131],"reduces":[132],"loss":[135],"relative":[136],"standard":[138],"perturbations,":[140],"(iii)":[142],"near-equivalence":[143],"when":[144],"two":[146],"nearly":[149],"orthogonal.":[150],"Across":[151],"vision":[152],"language":[154],"benchmarks":[155],"(CIFAR-10/100,":[156],"Tiny-ImageNet,":[157],"TOFU,":[158],"WMDP),":[159],"empirical":[161],"pattern":[162],"follows":[163],"this":[164],"geometry:":[165],"gives":[167],"its":[168],"clearest":[169],"gains":[170],"high-coupling":[172],"regimes":[173],"competitive":[176],"elsewhere.":[177]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-09T00:00:00"}