{"id":"https://openalex.org/W4410950233","doi":"https://doi.org/10.1109/ton.2025.3567071","title":"Machine Learning Model Trading With Verification Under Information Asymmetry","display_name":"Machine Learning Model Trading With Verification Under Information Asymmetry","publication_year":2025,"publication_date":"2025-06-02","ids":{"openalex":"https://openalex.org/W4410950233","doi":"https://doi.org/10.1109/ton.2025.3567071"},"language":"en","primary_location":{"id":"doi:10.1109/ton.2025.3567071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2025.3567071","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104079492","display_name":"Xiang Li","orcid":"https://orcid.org/0009-0002-1566-9607"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) and the School of Science and Engineering (SSE), The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0002-1566-9607","affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) and the School of Science and Engineering (SSE), The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062346297","display_name":"Jianwei Huang","orcid":"https://orcid.org/0000-0001-6631-1096"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwei Huang","raw_affiliation_strings":["SSE, AIRS, Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network, The Chinese University of Hong Kong, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0001-6631-1096","affiliations":[{"raw_affiliation_string":"SSE, AIRS, Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network, The Chinese University of Hong Kong, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100420873","display_name":"Kai Yang","orcid":"https://orcid.org/0000-0002-5983-198X"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Yang","raw_affiliation_strings":["Department of Computer Science and Technology, Key Laboratory of Embedded System and Service Computing, Ministry of Education, and Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5983-198X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Key Laboratory of Embedded System and Service Computing, Ministry of Education, and Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064015146","display_name":"Chenyou Fan","orcid":"https://orcid.org/0000-0002-9835-8507"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyou Fan","raw_affiliation_strings":["South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9835-8507","affiliations":[{"raw_affiliation_string":"South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05579968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"5","first_page":"2474","last_page":"2488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.44620001316070557,"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/T10320","display_name":"Neural Networks and Applications","score":0.44620001316070557,"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/T14351","display_name":"Statistical and Computational Modeling","score":0.4422999918460846,"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/information-asymmetry","display_name":"Information asymmetry","score":0.6680039167404175},{"id":"https://openalex.org/keywords/asymmetry","display_name":"Asymmetry","score":0.613422691822052},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5222971439361572},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3969901204109192},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3626074194908142},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.20174947381019592},{"id":"https://openalex.org/keywords/microeconomics","display_name":"Microeconomics","score":0.14546102285385132},{"id":"https://openalex.org/keywords/particle-physics","display_name":"Particle physics","score":0.06697815656661987},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05886048078536987}],"concepts":[{"id":"https://openalex.org/C137577040","wikidata":"https://www.wikidata.org/wiki/Q431965","display_name":"Information asymmetry","level":2,"score":0.6680039167404175},{"id":"https://openalex.org/C38976095","wikidata":"https://www.wikidata.org/wiki/Q752641","display_name":"Asymmetry","level":2,"score":0.613422691822052},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5222971439361572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3969901204109192},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3626074194908142},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.20174947381019592},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.14546102285385132},{"id":"https://openalex.org/C109214941","wikidata":"https://www.wikidata.org/wiki/Q18334","display_name":"Particle physics","level":1,"score":0.06697815656661987},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05886048078536987}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ton.2025.3567071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ton.2025.3567071","pdf_url":null,"source":{"id":"https://openalex.org/S5407042750","display_name":"IEEE Transactions on Networking","issn_l":"2998-4157","issn":["2998-4157"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Networking","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4377131734","display_name":null,"funder_award_id":"12371519","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5975532895","display_name":"\u9762\u5411\u5220\u9664\u4fe1\u9053\u7684\u6781\u5316\u7801\u8bd1\u7801\u7b97\u6cd5\u7406\u8bba\u4e0e\u8bef\u7801\u6027\u80fd\u7814\u7a76","funder_award_id":"61771013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5989840735","display_name":null,"funder_award_id":"ZDSYS20220606100601002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8222963720","display_name":null,"funder_award_id":"62271434","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1457398716","https://openalex.org/W1983755491","https://openalex.org/W2001153856","https://openalex.org/W2015518777","https://openalex.org/W2065504152","https://openalex.org/W2079104779","https://openalex.org/W2080217302","https://openalex.org/W2088262896","https://openalex.org/W2109735604","https://openalex.org/W2118649542","https://openalex.org/W2138517781","https://openalex.org/W2157121531","https://openalex.org/W2157497706","https://openalex.org/W2160567811","https://openalex.org/W2166312020","https://openalex.org/W2177723277","https://openalex.org/W2194775991","https://openalex.org/W2293940046","https://openalex.org/W2487440882","https://openalex.org/W2743929098","https://openalex.org/W2787894218","https://openalex.org/W2790400697","https://openalex.org/W2808948371","https://openalex.org/W2889110589","https://openalex.org/W2948176562","https://openalex.org/W2964210282","https://openalex.org/W3081690383","https://openalex.org/W3145740377","https://openalex.org/W3169708052","https://openalex.org/W3195579788","https://openalex.org/W4237379591","https://openalex.org/W4283220764","https://openalex.org/W4309505042","https://openalex.org/W4310491443","https://openalex.org/W4311926324","https://openalex.org/W4385286859","https://openalex.org/W4387870685","https://openalex.org/W4407811240"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Machine":[0],"learning":[1],"(ML)":[2],"model":[3,24,39,56,62,92,98,169],"trading,":[4],"known":[5],"for":[6,79,125,152,175],"its":[7],"role":[8],"in":[9,53,167],"protecting":[10,144],"data":[11],"privacy,":[12],"faces":[13],"a":[14,26,46,50,87],"major":[15],"challenge:":[16],"information":[17,135,147,165],"asymmetry.":[18],"This":[19,100],"issue":[20],"can":[21,69],"lead":[22],"to":[23,41,81],"deception,":[25],"problem":[27],"that":[28,58,86,133],"current":[29],"literature":[30],"has":[31],"not":[32],"fully":[33],"solved,":[34],"where":[35],"the":[36,54,95,105,111,139,150,153,156,161],"seller":[37,88,116,140],"misrepresents":[38],"performance":[40],"earn":[42],"more.":[43],"We":[44],"propose":[45],"game-theoretic":[47],"approach,":[48],"adding":[49],"verification":[51,106,112],"step":[52],"ML":[55,168],"market":[57],"lets":[59],"buyers":[60,80],"check":[61],"quality":[63],"before":[64],"buying.":[65],"However,":[66],"this":[67],"method":[68],"be":[70],"expensive":[71],"and":[72,108,141,171],"offers":[73],"imperfect":[74],"information,":[75],"making":[76],"it":[77],"harder":[78],"decide.":[82],"Our":[83],"analysis":[84],"reveals":[85],"might":[89],"probabilistically":[90],"conduct":[91],"deception":[93,101],"considering":[94],"chance":[96],"of":[97,163],"verification.":[99],"probability":[102],"decreases":[103],"with":[104,110],"accuracy":[107],"increases":[109],"cost.":[113],"To":[114],"maximize":[115],"payoff,":[117],"we":[118,131],"further":[119],"design":[120],"optimal":[121],"pricing":[122],"schemes":[123],"accounting":[124],"heterogeneous":[126],"buyers\u2019":[127],"strategic":[128],"behaviors.":[129],"Interestingly,":[130],"find":[132],"reducing":[134,164],"asymmetry":[136,166],"benefits":[137],"both":[138],"buyer.":[142],"Meanwhile,":[143],"buyer":[145,154],"order":[146],"doesn\u2019t":[148],"improve":[149],"payoff":[151],"or":[155],"seller.":[157],"These":[158],"findings":[159],"highlight":[160],"importance":[162],"trading":[170],"open":[172],"new":[173],"directions":[174],"future":[176],"research.":[177]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
