{"id":"https://openalex.org/W7166817984","doi":"https://doi.org/10.18653/v1/2026.findings-acl.832","title":"Doc-PP: Document Policy Preservation Benchmark for Large Vision-Language Models","display_name":"Doc-PP: Document Policy Preservation Benchmark for Large Vision-Language Models","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7166817984","doi":"https://doi.org/10.18653/v1/2026.findings-acl.832"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2026.findings-acl.832","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.832","pdf_url":"https://aclanthology.org/2026.findings-acl.832.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":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2026.findings-acl.832.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122316852","display_name":"Haeun Jang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haeun Jang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033496243","display_name":"Hwan Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwan Chang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139835103","display_name":"Hwanhee Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hwanhee Lee","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":0.80742632,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"16859","last_page":"16881"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13629","display_name":"Text Readability and Simplification","score":0.18889999389648438,"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/T13629","display_name":"Text Readability and Simplification","score":0.18889999389648438,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.10209999978542328,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.09759999811649323,"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/benchmark","display_name":"Benchmark (surveying)","score":0.4666999876499176},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2906999886035919},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2897000014781952},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.2840000092983246},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.2395000010728836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6434999704360962},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3517000079154968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31310001015663147},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2395000010728836},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2312999963760376},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.23109999299049377}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2026.findings-acl.832","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.832","pdf_url":"https://aclanthology.org/2026.findings-acl.832.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"}],"best_oa_location":{"id":"doi:10.18653/v1/2026.findings-acl.832","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2026.findings-acl.832","pdf_url":"https://aclanthology.org/2026.findings-acl.832.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":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.4578305780887604}],"awards":[{"id":"https://openalex.org/G13572568","display_name":null,"funder_award_id":"RS-2021-II211341","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G4244160943","display_name":null,"funder_award_id":"RS-2021-II211341","funder_id":"https://openalex.org/F4320321202","funder_display_name":"Chung-Ang University"},{"id":"https://openalex.org/G552592315","display_name":null,"funder_award_id":"RS-2021-II211341","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321202","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98"},{"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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166817984.pdf","grobid_xml":"https://content.openalex.org/works/W7166817984.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"deployment":[1],"of":[2,49],"Large":[3],"Vision-Language":[4],"Models":[5],"(LVLMs)":[6],"for":[7,151],"real-world":[8,66],"document":[9,153],"question":[10],"answering":[11],"is":[12,32],"often":[13],"constrained":[14],"by":[15],"dynamic,":[16],"user-defined":[17],"policies":[18],"that":[19,111,132,140],"dictate":[20],"information":[21,91],"disclosure":[22],"based":[23],"on":[24,39],"context.While":[25],"ensuring":[26],"adherence":[27],"to":[28],"these":[29,122],"explicit":[30],"constraints":[31],"critical,":[33],"existing":[34,106],"safety":[35,107],"research":[36],"primarily":[37],"focuses":[38],"implicit":[40],"social":[41],"norms":[42],"or":[43,100],"text-only":[44],"settings,":[45],"overlooking":[46],"the":[47],"complexities":[48],"multimodal":[50],"documents.In":[51],"this":[52],"paper,":[53],"we":[54,109,124],"introduce":[55],"Doc-PP":[56],"(Document":[57],"Policy":[58],"Preservation":[59],"Benchmark),":[60],"a":[61,82,128,148],"novel":[62],"benchmark":[63],"constructed":[64],"from":[65,135],"reports":[67],"requiring":[68],"reasoning":[69,134],"across":[70,102],"heterogeneous":[71],"visual":[72],"and":[73],"textual":[74],"elements":[75],"under":[76],"strict":[77],"non-disclosure":[78],"policies.Our":[79],"evaluation":[80],"highlights":[81],"systemic":[83],"Reasoning-Induced":[84],"Safety":[85],"Gap:":[86],"models":[87],"frequently":[88],"leak":[89],"sensitive":[90],"when":[92],"answers":[93],"must":[94],"be":[95],"inferred":[96],"through":[97],"complex":[98],"synthesis":[99],"aggregated":[101],"modalities,":[103],"effectively":[104],"circumventing":[105],"constraints.Furthermore,":[108],"identify":[110],"providing":[112],"extracted":[113],"text":[114],"improves":[115],"perception":[116],"but":[117],"inadvertently":[118],"facilitates":[119],"leakage.To":[120],"address":[121],"vulnerabilities,":[123],"propose":[125],"DVA":[126,141],"(Decompose-Verify-Aggregation),":[127],"structural":[129],"inference":[130],"framework":[131],"decouples":[133],"policy":[136],"verification.Experimental":[137],"results":[138],"demonstrate":[139],"significantly":[142],"outperforms":[143],"standard":[144],"prompting":[145],"defenses,":[146],"offering":[147],"robust":[149],"baseline":[150],"policy-compliant":[152],"understanding.":[154]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-02T00:00:00"}
