{"id":"https://openalex.org/W7155553653","doi":"https://doi.org/10.48550/arxiv.2604.20904","title":"Reinforcing privacy reasoning in LLMs via normative simulacra from fiction","display_name":"Reinforcing privacy reasoning in LLMs via normative simulacra from fiction","publication_year":2026,"publication_date":"2026-04-21","ids":{"openalex":"https://openalex.org/W7155553653","doi":"https://doi.org/10.48550/arxiv.2604.20904"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.20904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20904","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.2604.20904","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117285744","display_name":"Matt Franchi","orcid":"https://orcid.org/0000-0002-1376-0565"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Franchi, Matt","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014659992","display_name":"Madiha Zahrah Choksi","orcid":"https://orcid.org/0009-0008-4752-7164"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choksi, Madiha Zahrah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134504705","display_name":"Harold Triedman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Triedman, Harold","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134382557","display_name":"Helen Nissenbaum","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nissenbaum, Helen","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/T11045","display_name":"Privacy, Security, and Data Protection","score":0.4593999981880188,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11045","display_name":"Privacy, Security, and Data Protection","score":0.4593999981880188,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.09200000017881393,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10927","display_name":"Access Control and Trust","score":0.05990000069141388,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/normative","display_name":"Normative","score":0.7894999980926514},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5307000279426575},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.4433000087738037},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.42910000681877136},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.3506999909877777},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.34769999980926514},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.34709998965263367}],"concepts":[{"id":"https://openalex.org/C44725695","wikidata":"https://www.wikidata.org/wiki/Q288156","display_name":"Normative","level":2,"score":0.7894999980926514},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5307000279426575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5157999992370605},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.4433000087738037},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.42910000681877136},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.39800000190734863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39480000734329224},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.37950000166893005},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.3531000018119812},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.3506999909877777},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C137549413","wikidata":"https://www.wikidata.org/wiki/Q7053127","display_name":"Normative model of decision-making","level":3,"score":0.3287000060081482},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.31769999861717224},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.299699991941452},{"id":"https://openalex.org/C2777146004","wikidata":"https://www.wikidata.org/wiki/Q14949826","display_name":"CLARITY","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C156325361","wikidata":"https://www.wikidata.org/wiki/Q1152864","display_name":"Grounded theory","level":3,"score":0.2669999897480011},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.20904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20904","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.2604.20904","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.20904","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":[{"id":"https://metadata.un.org/sdg/16","score":0.5558698773384094,"display_name":"Peace, Justice and strong institutions"},{"id":"https://metadata.un.org/sdg/10","score":0.4051750898361206,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Information":[0],"handling":[1],"practices":[2],"of":[3,14,30,58,123,177,196,203],"LLM":[4,107],"agents":[5],"are":[6],"broadly":[7],"misaligned":[8],"with":[9,105,207,222],"the":[10,27,112,119,124,141,152,175,201,211],"contextual":[11,234],"privacy":[12,25,114,204,225,235],"expectations":[13],"their":[15],"users.":[16],"Contextual":[17],"Integrity":[18],"(CI)":[19],"provides":[20],"a":[21,146,187,215],"principled":[22],"framework,":[23],"defining":[24],"as":[26],"appropriate":[28],"flow":[29],"information":[31,61,192],"within":[32],"context-relative":[33],"norms.":[34,162],"However,":[35],"existing":[36],"approaches":[37],"either":[38],"double":[39],"inference":[40],"cost":[41],"via":[42,72],"supervisor-assistant":[43],"architectures,":[44],"or":[45],"fine-tune":[46,70],"on":[47,156,165,214],"narrow":[48],"task-specific":[49],"data.":[50],"We":[51,163],"propose":[52],"extracting":[53],"normative":[54,121,143,180,208,230],"simulacra":[55,231],"(structured":[56],"representations":[57],"norms":[59],"and":[60,66,95,102,145,173,179,219],"flows)":[62],"from":[63],"fiction":[64],"novels":[65],"using":[67],"them":[68],"to":[69,154,239],"LLMs":[71],"supervised":[73],"learning":[74],"followed":[75],"by":[76],"GRPO":[77,206],"reinforcement":[78],"learning.":[79],"Our":[80],"composite":[81],"reward":[82],"function":[83],"combines":[84],"programmatic":[85],"signals,":[86],"including":[87],"task":[88],"clarity":[89],"(subsuming":[90],"schema":[91],"validity,":[92],"construct":[93],"discrimination,":[94],"extraction":[96],"confidence),":[97],"structural":[98],"completeness,":[99],"internal":[100],"consistency,":[101],"context":[103,157],"identification,":[104],"an":[106],"judge":[108],"that":[109,228,237],"evaluates":[110],"whether":[111],"model's":[113],"reasoning":[115,236],"is":[116,137],"grounded":[117],"in":[118],"held-out":[120],"universe":[122,144],"source":[125],"text.":[126],"To":[127],"mitigate":[128],"overfitting,":[129],"we":[130],"introduce":[131],"per-completion":[132],"contrastive":[133],"scoring:":[134],"each":[135],"completion":[136],"evaluated":[138],"against":[139],"both":[140],"correct":[142],"randomly":[147],"selected":[148],"wrong":[149],"one,":[150],"teaching":[151],"model":[153],"condition":[155],"rather":[158],"than":[159],"memorize":[160],"source-specific":[161],"evaluate":[164],"five":[166],"CI-aligned":[167],"benchmarks":[168],"spanning":[169],"distinct":[170],"societal":[171],"contexts":[172],"ablate":[174],"contributions":[176],"RL":[178],"grounding.":[181],"Across":[182],"seven":[183],"models,":[184],"SFT":[185],"introduces":[186],"conservative":[188],"prior":[189],"toward":[190],"restricting":[191],"flow,":[193],"improving":[194],"recognition":[195],"privacy-relevant":[197],"situations":[198],"but":[199],"not":[200],"correctness":[202],"judgments.":[205],"grounding":[209],"achieves":[210],"highest":[212],"score":[213],"law":[216],"compliance":[217],"benchmark":[218],"strongest":[220],"correlation":[221],"crowdsourced":[223],"human":[224],"expectations,":[226],"demonstrating":[227],"fiction-derived":[229],"can":[232],"teach":[233],"transfers":[238],"real-world":[240],"domains.":[241]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-25T00:00:00"}