{"id":"https://openalex.org/W7162025838","doi":"https://doi.org/10.48550/arxiv.2605.20258","title":"It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs","display_name":"It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs","publication_year":2026,"publication_date":"2026-05-18","ids":{"openalex":"https://openalex.org/W7162025838","doi":"https://doi.org/10.48550/arxiv.2605.20258"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.20258","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20258","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.20258","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136647106","display_name":"Sangwoo Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Sangwoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128102287","display_name":"Woongyeong Yeo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeo, Woongyeong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136617826","display_name":"Seanie Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Seanie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124866247","display_name":"Yumin Choi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choi, Yumin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136688359","display_name":"Hyomin Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Hyomin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136659188","display_name":"Kangsan Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Kangsan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013449404","display_name":"Jinheon Baek","orcid":"https://orcid.org/0000-0002-9367-560X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baek, Jinheon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136634119","display_name":"Seong Joon Oh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oh, Seong Joon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136699125","display_name":"Sung Ju Hwang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwang, Sung Ju","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.22789999842643738,"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":0.22789999842643738,"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.12549999356269836,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.1168999969959259,"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/intersection","display_name":"Intersection (aeronautics)","score":0.7437000274658203},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6844000220298767},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.560699999332428},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.46320000290870667},{"id":"https://openalex.org/keywords/information-sensitivity","display_name":"Information sensitivity","score":0.435699999332428},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4162999987602234},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.3898000121116638},{"id":"https://openalex.org/keywords/personally-identifiable-information","display_name":"Personally identifiable information","score":0.34860000014305115}],"concepts":[{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7437000274658203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6962000131607056},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6844000220298767},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.560699999332428},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.46320000290870667},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.3898000121116638},{"id":"https://openalex.org/C169093310","wikidata":"https://www.wikidata.org/wiki/Q3702971","display_name":"Personally identifiable information","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.34850001335144043},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.3375000059604645},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.32919999957084656},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3041999936103821},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.29120001196861267},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2872999906539917},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26809999346733093},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.20258","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20258","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.20258","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.20258","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":"article"},"sustainable_development_goals":[{"score":0.5399987697601318,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Contextual":[0],"Integrity":[1],"(CI)":[2],"defines":[3],"privacy":[4,127],"not":[5],"merely":[6],"as":[7,12,31,145],"keeping":[8],"information":[9,14,75,99],"hidden,":[10],"but":[11],"governing":[13],"flows":[15],"according":[16],"to":[17,38,156],"the":[18,103,119,122],"norms":[19],"of":[20,124],"a":[21,69,114,170],"given":[22],"context.":[23],"As":[24],"large":[25],"language":[26],"models":[27,45],"are":[28],"increasingly":[29],"deployed":[30],"personal":[32],"agents":[33],"handling":[34],"sensitive":[35],"workflows,":[36],"adhering":[37],"CI":[39,174],"becomes":[40],"critical.":[41],"However,":[42],"even":[43],"frontier":[44],"remain":[46],"unreliable":[47],"in":[48],"making":[49],"disclosure":[50],"decisions,":[51],"and":[52,107,126,162],"existing":[53],"mitigation":[54],"strategies":[55],"often":[56],"degrade":[57],"underlying":[58],"task":[59,78],"performance.":[60],"To":[61],"overcome":[62],"this":[63],"privacy-utility":[64],"trade-off,":[65],"we":[66],"propose":[67],"SELFCI,":[68,133],"complementary":[70,111],"self-distillation":[71],"framework":[72],"that":[73,132,167],"decouples":[74],"suppression":[76],"from":[77,93],"resolution.":[79],"SELFCI":[80,168],"jointly":[81],"optimizes":[82],"two":[83],"independent":[84],"reverse":[85],"KL":[86],"divergences":[87],"over":[88],"distinct":[89],"teacher":[90],"distributions":[91],"derived":[92],"feedback:":[94],"one":[95],"encourages":[96],"preserving":[97],"task-relevant":[98],"for":[100],"utility,":[101],"while":[102],"other":[104],"enforces":[105],"minimal":[106],"appropriate":[108],"disclosure.":[109],"This":[110],"formulation":[112],"induces":[113],"Product-of-Experts":[115],"(PoE)":[116],"target,":[117],"aligning":[118],"policy":[120],"with":[121],"intersection":[123],"capability":[125],"requirements.":[128],"Empirical":[129],"evaluations":[130],"demonstrate":[131],"without":[134],"relying":[135],"on":[136],"costly":[137],"external":[138],"supervision,":[139],"consistently":[140],"outperforms":[141],"competitive":[142],"baselines":[143],"such":[144],"online":[146],"reinforcement":[147],"learning":[148],"algorithms":[149],"(e.g.,":[150],"GRPO).":[151],"These":[152],"trends":[153],"further":[154],"extend":[155],"out-of-domain":[157],"settings":[158],"involving":[159],"agentic":[160],"workflows":[161],"accumulated":[163],"private":[164],"context,":[165],"suggesting":[166],"provides":[169],"practical":[171],"path":[172],"toward":[173],"alignment.":[175]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-22T00:00:00"}
