{"id":"https://openalex.org/W7164178156","doi":"https://doi.org/10.48550/arxiv.2606.09868","title":"SPACE: Source-free Proxy Anchor Concept Erasure for MLLMs","display_name":"SPACE: Source-free Proxy Anchor Concept Erasure for MLLMs","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7164178156","doi":"https://doi.org/10.48550/arxiv.2606.09868"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09868","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09868","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.2606.09868","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138373705","display_name":"Zhijing Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zhijing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138294581","display_name":"Jiaqi Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138351888","display_name":"Qianshan Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei, Qianshan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138360388","display_name":"Nan Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Nan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138346333","display_name":"Jiaqi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jiaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138351848","display_name":"Yongliang Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yongliang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138316606","display_name":"Tongxin Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Tongxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5112049375","display_name":"Xiaolin Fang","orcid":"https://orcid.org/0000-0002-0164-2596"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Xiaolin","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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.2401999980211258,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.2401999980211258,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.10199999809265137,"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":0.07240000367164612,"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/erasure","display_name":"Erasure","score":0.6503000259399414},{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.4909999966621399},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.41519999504089355},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.3431999981403351},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.33820000290870667},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.32089999318122864}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7264000177383423},{"id":"https://openalex.org/C2778790127","wikidata":"https://www.wikidata.org/wiki/Q484885","display_name":"Erasure","level":2,"score":0.6503000259399414},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.4909999966621399},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4251999855041504},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.33820000290870667},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3370000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3246999979019165},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.32089999318122864},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3140999972820282},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2930999994277954},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.28600001335144043},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C2779628075","wikidata":"https://www.wikidata.org/wiki/Q1253258","display_name":"Downgrade","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2632000148296356}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09868","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09868","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.2606.09868","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09868","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7813927531242371}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"Multimodal":[1],"Large":[2],"Language":[3],"Models":[4],"(MLLMs)":[5],"face":[6],"growing":[7],"privacy":[8],"risks":[9],"and":[10,149],"regulatory":[11],"constraints,":[12],"machine":[13],"unlearning":[14,59,83],"(MU)":[15],"has":[16],"emerged":[17],"as":[18],"a":[19,55],"crucial":[20],"solution":[21],"for":[22,57,86],"removing":[23],"sensitive":[24],"data":[25,38,50],"while":[26],"preserving":[27],"model":[28],"performance.":[29,158],"However,":[30],"existing":[31],"MU":[32,182],"methods":[33],"typically":[34],"rely":[35],"on":[36,146],"visual":[37],"of":[39,90,131,173],"the":[40,66,80,106,128,144,156],"target":[41,67,122],"concepts,":[42],"which":[43,99,115],"is":[44],"often":[45],"unavailable":[46],"due":[47],"to":[48,65,119,127,171],"strict":[49],"retention":[51],"policies,":[52],"thus":[53],"creating":[54],"demand":[56],"source-free":[58,82,181],"approaches":[60],"that":[61,140,166,172],"operate":[62],"without":[63],"access":[64],"data.":[68],"In":[69],"this":[70],"work,":[71],"we":[72],"propose":[73],"Source-free":[74],"Proxy":[75,95],"Anchor":[76,96],"Concept":[77],"Erasure":[78],"(SPACE),":[79],"first":[81],"framework":[84],"specialized":[85],"MLLMs.":[87],"SPACE":[88,141,167],"consists":[89],"two":[91],"stages:":[92],"(1)":[93],"Text-Guided":[94],"Selection":[97],"(TPAS),":[98],"retrieves":[100],"semantically":[101],"aligned":[102],"proxy":[103],"anchors":[104,118],"from":[105],"shared":[107],"feature":[108,151],"space.":[109],"(2)":[110],"Dual-Constraint":[111],"Semantic":[112],"Isolation":[113],"(DCSI),":[114],"optimizes":[116],"these":[117],"indirectly":[120],"erase":[121],"concepts.":[123],"DCSI":[124],"confines":[125],"updates":[126],"null":[129],"space":[130],"retained":[132,147],"knowledge,":[133],"ensuring":[134],"structural":[135],"integrity.":[136],"We":[137],"theoretically":[138],"prove":[139],"strictly":[142],"bounds":[143],"perturbation":[145],"knowledge":[148],"maximizes":[150],"spectral":[152],"entropy,":[153],"thereby":[154],"maintaining":[155],"model's":[157],"Furthermore,":[159],"extensive":[160],"experiments":[161],"across":[162],"six":[163],"datasets":[164],"show":[165],"achieves":[168],"performance":[169],"comparable":[170],"state-of-the-art":[174],"data-dependent":[175],"methods,":[176],"validating":[177],"its":[178],"effectiveness":[179],"in":[180],"scenarios.":[183],"The":[184],"source":[185],"code":[186],"will":[187],"be":[188],"released.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-11T00:00:00"}
