{"id":"https://openalex.org/W7154987533","doi":"https://doi.org/10.48550/arxiv.2604.15461","title":"Evaluating LLM Simulators as Differentially Private Data Generators","display_name":"Evaluating LLM Simulators as Differentially Private Data Generators","publication_year":2026,"publication_date":"2026-04-16","ids":{"openalex":"https://openalex.org/W7154987533","doi":"https://doi.org/10.48550/arxiv.2604.15461"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.15461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15461","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.15461","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033118456","display_name":"Nassima M. Bouzid","orcid":"https://orcid.org/0000-0001-5565-8676"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bouzid, Nassima M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066054182","display_name":"Dehao Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Dehao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134039798","display_name":"Nam H. Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Nam H.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5014759332","display_name":"Mayana Pereira","orcid":"https://orcid.org/0000-0001-8636-8882"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pereira, Mayana","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"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/T14074","display_name":"Persona Design and Applications","score":0.8828999996185303,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T14074","display_name":"Persona Design and Applications","score":0.8828999996185303,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11719","display_name":"Data Quality and Management","score":0.008500000461935997,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.00800000037997961,"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/prior-probability","display_name":"Prior probability","score":0.5971999764442444},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.5537999868392944},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4657999873161316},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.3937999904155731},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.349700003862381},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.3321000039577484},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.3174000084400177}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.656499981880188},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5971999764442444},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.5537999868392944},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4359000027179718},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37070000171661377},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3336000144481659},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.3174000084400177},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.301800012588501},{"id":"https://openalex.org/C3020493868","wikidata":"https://www.wikidata.org/wiki/Q55631277","display_name":"Real world data","level":2,"score":0.3012000024318695},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.2978000044822693},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.27880001068115234},{"id":"https://openalex.org/C121426985","wikidata":"https://www.wikidata.org/wiki/Q591763","display_name":"Private sector","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.15461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15461","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.15461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15461","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":"article"},"sustainable_development_goals":[{"score":0.7954894304275513,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LLM-based":[0,90],"simulators":[1],"offer":[2],"a":[3],"promising":[4,56],"path":[5],"for":[6,78],"generating":[7],"complex":[8],"synthetic":[9,44],"data":[10],"where":[11,98],"traditional":[12],"differentially":[13],"private":[14],"(DP)":[15],"methods":[16,91],"struggle":[17],"with":[18,42],"high-dimensional":[19],"user":[20,49,96],"profiles.":[21],"But":[22],"can":[23,92],"LLMs":[24],"faithfully":[25],"reproduce":[26],"statistical":[27],"distributions":[28],"from":[29,47],"DP-protected":[30],"inputs?":[31],"We":[32,51],"evaluate":[33],"this":[34],"using":[35],"PersonaLedger,":[36],"an":[37],"agentic":[38],"financial":[39],"simulator,":[40],"seeded":[41],"DP":[43],"personas":[45],"derived":[46],"real":[48],"statistics.":[50],"find":[52],"that":[53],"PersonaLedger":[54],"achieves":[55],"fraud":[57],"detection":[58],"utility":[59],"(AUC":[60],"0.70":[61],"at":[62],"epsilon=1)":[63],"but":[64],"exhibits":[65],"significant":[66],"distribution":[67],"drift":[68],"due":[69],"to":[70],"systematic":[71],"LLM":[72],"biases--learned":[73],"priors":[74],"overriding":[75],"input":[76],"statistics":[77],"temporal":[79],"and":[80],"demographic":[81],"features.":[82],"These":[83],"failure":[84],"modes":[85],"must":[86],"be":[87],"addressed":[88],"before":[89],"handle":[93],"the":[94],"richer":[95],"representations":[97],"they":[99],"might":[100],"otherwise":[101],"excel.":[102]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-21T00:00:00"}
