{"id":"https://openalex.org/W4399971973","doi":"https://doi.org/10.29012/jpc.880","title":"Differentially Private Fine-tuning of Language Models","display_name":"Differentially Private Fine-tuning of Language Models","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4399971973","doi":"https://doi.org/10.29012/jpc.880"},"language":"en","primary_location":{"id":"doi:10.29012/jpc.880","is_oa":true,"landing_page_url":"https://doi.org/10.29012/jpc.880","pdf_url":"https://journalprivacyconfidentiality.org/index.php/jpc/article/download/880/766","source":{"id":"https://openalex.org/S4210191919","display_name":"Journal of Privacy and Confidentiality","issn_l":"2575-8527","issn":["2575-8527"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Privacy and Confidentiality","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journalprivacyconfidentiality.org/index.php/jpc/article/download/880/766","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102141174","display_name":"Da Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Da Yu","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065300132","display_name":"Saurabh Naik","orcid":"https://orcid.org/0000-0002-0465-2810"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Saurabh Naik","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084855970","display_name":"Art\u016brs Ba\u010dkurs","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Arturs Backurs","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038687630","display_name":"Sivakanth Gopi","orcid":"https://orcid.org/0000-0001-9706-4171"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sivakanth Gopi","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071827392","display_name":"Huseyin A. Inan","orcid":"https://orcid.org/0000-0001-7465-7214"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huseyin A. Inan","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047778197","display_name":"Gautam Kamath","orcid":"https://orcid.org/0000-0003-0048-2559"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gautam Kamath","raw_affiliation_strings":["University of Waterloo"],"raw_orcid":"https://orcid.org/0000-0003-0048-2559","affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043137436","display_name":"Janardhan Kulkarni","orcid":"https://orcid.org/0009-0005-9980-7836"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Janardhan Kulkarni","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024980585","display_name":"Yin Tat Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yin Tat Lee","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023529203","display_name":"Andre Manoel","orcid":"https://orcid.org/0000-0002-5455-0230"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andre Manoel","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057803811","display_name":"Lukas Wutschitz","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lukas Wutschitz","raw_affiliation_strings":["Microsoft"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046685409","display_name":"Sergey Yekhanin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sergey Yekhanin","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033280929","display_name":"Huishuai Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huishuai Zhang","raw_affiliation_strings":["Microsoft Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":12,"corresponding_author_ids":["https://openalex.org/A5102141174"],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":9.4406,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.98337629,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"14","issue":"2","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":0.9997000098228455,"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":0.9997000098228455,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9259999990463257,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9218999743461609,"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/computer-science","display_name":"Computer science","score":0.678368330001831},{"id":"https://openalex.org/keywords/private-speech","display_name":"Private speech","score":0.5540030002593994},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.5363174080848694},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5251034498214722},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.5086086988449097},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4734765291213989},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4623502492904663},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42926862835884094},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3399196267127991},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3350456953048706},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.20618951320648193},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1385592222213745}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.678368330001831},{"id":"https://openalex.org/C35992214","wikidata":"https://www.wikidata.org/wiki/Q7246254","display_name":"Private speech","level":2,"score":0.5540030002593994},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.5363174080848694},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5251034498214722},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.5086086988449097},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4734765291213989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4623502492904663},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42926862835884094},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3399196267127991},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3350456953048706},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.20618951320648193},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1385592222213745},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138496976","wikidata":"https://www.wikidata.org/wiki/Q175002","display_name":"Developmental psychology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.29012/jpc.880","is_oa":true,"landing_page_url":"https://doi.org/10.29012/jpc.880","pdf_url":"https://journalprivacyconfidentiality.org/index.php/jpc/article/download/880/766","source":{"id":"https://openalex.org/S4210191919","display_name":"Journal of Privacy and Confidentiality","issn_l":"2575-8527","issn":["2575-8527"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Privacy and Confidentiality","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8346b4e076df4c3695c222783f15b79f","is_oa":true,"landing_page_url":"https://doaj.org/article/8346b4e076df4c3695c222783f15b79f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"The Journal of Privacy and Confidentiality, Vol 14, Iss 2 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.29012/jpc.880","is_oa":true,"landing_page_url":"https://doi.org/10.29012/jpc.880","pdf_url":"https://journalprivacyconfidentiality.org/index.php/jpc/article/download/880/766","source":{"id":"https://openalex.org/S4210191919","display_name":"Journal of Privacy and Confidentiality","issn_l":"2575-8527","issn":["2575-8527"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Privacy and Confidentiality","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.4000000059604645}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399971973.pdf"},"referenced_works_count":83,"referenced_works":["https://openalex.org/W1557833142","https://openalex.org/W1873763122","https://openalex.org/W1985511977","https://openalex.org/W2021426916","https://openalex.org/W2115358662","https://openalex.org/W2148437670","https://openalex.org/W2473418344","https://openalex.org/W2750779823","https://openalex.org/W2763421725","https://openalex.org/W2768663569","https://openalex.org/W2784621220","https://openalex.org/W2785361959","https://openalex.org/W2805580603","https://openalex.org/W2891003389","https://openalex.org/W2899663614","https://openalex.org/W2908510526","https://openalex.org/W2923014074","https://openalex.org/W2946930197","https://openalex.org/W2963341956","https://openalex.org/W2963477238","https://openalex.org/W2963807318","https://openalex.org/W2963846996","https://openalex.org/W2963912046","https://openalex.org/W2964303773","https://openalex.org/W2965373594","https://openalex.org/W2965528577","https://openalex.org/W2982273290","https://openalex.org/W2986886197","https://openalex.org/W2997195635","https://openalex.org/W2999251207","https://openalex.org/W3034751955","https://openalex.org/W3035261884","https://openalex.org/W3041206960","https://openalex.org/W3046392445","https://openalex.org/W3110164654","https://openalex.org/W3113004165","https://openalex.org/W3113151582","https://openalex.org/W3125098139","https://openalex.org/W3166560088","https://openalex.org/W3167530662","https://openalex.org/W3168867926","https://openalex.org/W3170764772","https://openalex.org/W3174770825","https://openalex.org/W3175645569","https://openalex.org/W3177323791","https://openalex.org/W3188505388","https://openalex.org/W3196927184","https://openalex.org/W3207429447","https://openalex.org/W4205991051","https://openalex.org/W4206178588","https://openalex.org/W4225150360","https://openalex.org/W4226149970","https://openalex.org/W4226277587","https://openalex.org/W4229442835","https://openalex.org/W4231844697","https://openalex.org/W4233907442","https://openalex.org/W4249014631","https://openalex.org/W4281722692","https://openalex.org/W4281984841","https://openalex.org/W4283816219","https://openalex.org/W4287112812","https://openalex.org/W4287122891","https://openalex.org/W4287553002","https://openalex.org/W4287663285","https://openalex.org/W4292779060","https://openalex.org/W4297781211","https://openalex.org/W4297799122","https://openalex.org/W4302010013","https://openalex.org/W4302016406","https://openalex.org/W4302305417","https://openalex.org/W4310822350","https://openalex.org/W4311555033","https://openalex.org/W4312266295","https://openalex.org/W4322717491","https://openalex.org/W4379474720","https://openalex.org/W4385245566","https://openalex.org/W4385573380","https://openalex.org/W4386081881","https://openalex.org/W4386435720","https://openalex.org/W4386755323","https://openalex.org/W4387323203","https://openalex.org/W4387994968","https://openalex.org/W4391382837"],"related_works":["https://openalex.org/W1995720418","https://openalex.org/W2477421567","https://openalex.org/W2486623810","https://openalex.org/W1987856272","https://openalex.org/W3171115726","https://openalex.org/W1920452688","https://openalex.org/W2042657303","https://openalex.org/W2129061439","https://openalex.org/W4221016029","https://openalex.org/W4245156176"],"abstract_inverted_index":{"We":[0,29],"give":[1],"simpler,":[2],"sparser,":[3],"and":[4,67,70,105,144,153],"faster":[5],"algorithms":[6,60],"for":[7,33,45,132,179],"differentially":[8,51],"private":[9,52,59,74,84,180],"fine-tuning":[10,138],"of":[11,41,54,73,83,88,101,113,126,149,158],"large-scale":[12],"pre-trained":[13],"language":[14,134],"models,":[15],"which":[16],"achieve":[17,98,146,188],"the":[18,38,68,81,94,164],"state-of-the-art":[19],"privacy":[20,111,120,202],"versus":[21],"utility":[22,82],"tradeoffs":[23],"on":[24,93],"many":[25,77],"standard":[26],"NLP":[27],"tasks.":[28,136],"propose":[30],"a":[31,110],"meta-framework":[32],"this":[34],"problem,":[35],"inspired":[36],"by":[37],"recent":[39],"success":[40],"highly":[42],"parameter-efficient":[43],"methods":[44],"fine-tuning.":[46],"Our":[47,128],"experiments":[48,171],"show":[49],"that":[50,87,173,194],"adaptations":[53],"these":[55],"approaches":[56,86],"outperform":[57],"previous":[58],"in":[61],"three":[62],"important":[63],"dimensions:":[64],"utility,":[65],"privacy,":[66],"computational":[69],"memory":[71],"cost":[72],"training.":[75],"On":[76],"commonly":[78],"studied":[79],"datasets,":[80],"models":[85,175],"non-private":[89,165],"models.":[90],"For":[91],"example,":[92],"MNLI":[95],"dataset":[96],"we":[97,192],"an":[99,124],"accuracy":[100,125,190,200],"$87.8\\%$":[102],"using":[103,107],"RoBERTa-Large":[104,122],"$83.5\\%$":[106],"RoBERTa-Base":[108],"with":[109,139],"budget":[112,157],"$\\epsilon":[114,159],"=":[115,160],"6.7$.":[116],"In":[117],"comparison,":[118],"absent":[119],"constraints,":[121],"achieves":[123],"$90.2\\%$.":[127],"findings":[129],"are":[130,176,184],"similar":[131],"natural":[133],"generation":[135],"Privately":[137],"DART,":[140],"GPT-2-Small,":[141],"GPT-2-Medium,":[142],"GPT-2-Large,":[143],"GPT-2-XL":[145],"BLEU":[147],"scores":[148],"38.5,":[150],"42.0,":[151],"43.1,":[152],"43.8":[154],"respectively":[155],"(privacy":[156],"6.8,\\delta=$":[161],"1e-5)":[162],"whereas":[163],"baseline":[166],"is":[167,203],"$48.1$.":[168],"All":[169],"our":[170],"suggest":[172],"larger":[174],"better":[177,197],"suited":[178],"fine-tuning:":[181],"while":[182],"they":[183,195],"well":[185],"known":[186],"to":[187],"superior":[189],"non-privately,":[191],"find":[193],"also":[196],"maintain":[198],"their":[199],"when":[201],"introduced.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}