{"id":"https://openalex.org/W7129076650","doi":"https://doi.org/10.1145/3773966.3777920","title":"Privacy-preserved LLM Cascade via CoT-enhanced Policy Learning","display_name":"Privacy-preserved LLM Cascade via CoT-enhanced Policy Learning","publication_year":2026,"publication_date":"2026-02-16","ids":{"openalex":"https://openalex.org/W7129076650","doi":"https://doi.org/10.1145/3773966.3777920"},"language":null,"primary_location":{"id":"doi:10.1145/3773966.3777920","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777920","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3773966.3777920","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126082179","display_name":"Kai Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Zhang","raw_affiliation_strings":["Worcester Polytechnic Institute, Worcester, MA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4783-6705","affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Worcester, MA, USA","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126124859","display_name":"Conchao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Congchao Wang","raw_affiliation_strings":["Google AIR, Mountain View, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1318-7180","affiliations":[{"raw_affiliation_string":"Google AIR, Mountain View, CA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126088753","display_name":"Liqian Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liqian Peng","raw_affiliation_strings":["Google AIR, Mountain View, MA, USA"],"raw_orcid":"https://orcid.org/0009-0005-4764-4844","affiliations":[{"raw_affiliation_string":"Google AIR, Mountain View, MA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025070646","display_name":"Alec Go","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alec Go","raw_affiliation_strings":["Google AIR, Mountaion View, MA, USA"],"raw_orcid":"https://orcid.org/0009-0008-2641-5948","affiliations":[{"raw_affiliation_string":"Google AIR, Mountaion View, MA, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101985030","display_name":"Xiaozhong Liu","orcid":"https://orcid.org/0000-0003-3477-8323"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaozhong Liu","raw_affiliation_strings":["Worcester Polytechnic Institute, Worcester, MA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3477-8323","affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Worcester, MA, USA","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"955","last_page":"964"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.18389999866485596,"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":0.18389999866485596,"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/T14347","display_name":"Big Data and Digital Economy","score":0.1429000049829483,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.07209999859333038,"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/variety","display_name":"Variety (cybernetics)","score":0.722000002861023},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6604999899864197},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.5602999925613403},{"id":"https://openalex.org/keywords/information-cascade","display_name":"Information cascade","score":0.4417000114917755},{"id":"https://openalex.org/keywords/limit","display_name":"Limit (mathematics)","score":0.4339999854564667},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.39649999141693115},{"id":"https://openalex.org/keywords/private-information-retrieval","display_name":"Private information retrieval","score":0.3833000063896179},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.3732999861240387}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7781999707221985},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.722000002861023},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6604999899864197},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.5602999925613403},{"id":"https://openalex.org/C27286358","wikidata":"https://www.wikidata.org/wiki/Q6031027","display_name":"Information cascade","level":2,"score":0.4417000114917755},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.4339999854564667},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3946000039577484},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3571000099182129},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3336000144481659},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3244999945163727},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3199999928474426},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2865999937057495},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25540000200271606},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.250900000333786},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3773966.3777920","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777920","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3773966.3777920","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777920","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7610149383544922,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2164598857","https://openalex.org/W2979826702","https://openalex.org/W4388874804","https://openalex.org/W4390550007","https://openalex.org/W4399534449","https://openalex.org/W4401042391","https://openalex.org/W4401044155","https://openalex.org/W4402683378"],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"attracted":[5],"significant":[6],"attention":[7],"for":[8,55,111,118],"on-device":[9],"applications,":[10],"delivering":[11],"strong":[12],"performance":[13],"across":[14],"a":[15,41,50,78,99,108],"variety":[16],"of":[17],"real-world":[18,67],"tasks.":[19],"However,":[20],"hardware":[21],"constraints":[22],"on":[23,135],"edge":[24],"devices":[25],"limit":[26],"model":[27,44,54],"capacity,":[28],"often":[29],"resulting":[30],"in":[31,146],"suboptimal":[32],"performance.":[33],"A":[34],"promising":[35],"remedy":[36],"is":[37],"LLM":[38],"cascading,":[39],"where":[40],"lightweight":[42],"local":[43],"defers":[45],"selected":[46],"hard":[47],"queries":[48],"to":[49],"more":[51],"capable":[52],"server":[53],"response":[56],"generation.":[57],"While":[58],"prior":[59],"work":[60],"has":[61],"primarily":[62],"optimized":[63],"the":[64],"performance--cost":[65],"trade-off,":[66],"deployments":[68],"must":[69],"also":[70],"address":[71],"privacy":[72,131,150],"concerns":[73],"i.e.,":[74],"user":[75],"information":[76],"leakage,":[77],"requirement":[79],"that":[80,140],"remains":[81],"largely":[82],"overlooked.":[83],"In":[84],"this":[85],"work,":[86],"we":[87],"go":[88],"beyond":[89],"existing":[90,144],"confidence-":[91],"and":[92,96,121,149],"logit-based":[93],"cascade":[94,127],"methods":[95,145],"propose":[97],"P3Defer,":[98],"novel":[100],"Chain-of-Thought":[101],"(CoT)-enhanced":[102],"policy":[103],"learning":[104],"framework":[105],"coupled":[106],"with":[107],"private":[109],"memory":[110],"privacy-preserved":[112],"deferral":[113],"decision-making.":[114],"By":[115],"jointly":[116],"optimizing":[117],"performance,":[119],"cost,":[120],"privacy,":[122],"our":[123],"approach":[124],"improves":[125],"performance-cost":[126],"efficiency":[128],"while":[129],"mitigating":[130],"risks.":[132],"Extensive":[133],"experiments":[134],"three":[136],"benchmark":[137],"datasets":[138],"demonstrate":[139],"P3Defer":[141],"consistently":[142],"outperforms":[143],"both":[147],"accuracy":[148],"preservation.":[151]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-17T00:00:00"}
