{"id":"https://openalex.org/W4414230222","doi":"https://doi.org/10.1109/tpami.2025.3609625","title":"Task-Distributionally Robust Data-Free Meta-Learning","display_name":"Task-Distributionally Robust Data-Free Meta-Learning","publication_year":2025,"publication_date":"2025-09-16","ids":{"openalex":"https://openalex.org/W4414230222","doi":"https://doi.org/10.1109/tpami.2025.3609625","pmid":"https://pubmed.ncbi.nlm.nih.gov/40956731"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3609625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3609625","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5065181430","display_name":"Zixuan Hu","orcid":"https://orcid.org/0000-0002-3300-7298"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Zixuan Hu","raw_affiliation_strings":["College of Computing and Data Science, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"College of Computing and Data Science, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077761339","display_name":"Yongxian Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxian Wei","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042802004","display_name":"Li Shen","orcid":"https://orcid.org/0000-0001-5659-3464"},"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":false,"raw_author_name":"Li Shen","raw_affiliation_strings":["School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690302","display_name":"Zhenyi Wang","orcid":"https://orcid.org/0000-0002-2780-9446"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]},{"id":"https://openalex.org/I4210160220","display_name":"Central Florida Neurosurgery Institute","ror":"https://ror.org/052vdf235","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210160220"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenyi Wang","raw_affiliation_strings":["Department of Computer Science and AI Institute, University of Central Florida, Orlando, FL, USA","Department of Computer Science and AI Institute, University of Central Florida, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and AI Institute, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777","https://openalex.org/I4210160220"]},{"raw_affiliation_string":"Department of Computer Science and AI Institute, University of Central Florida, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068027800","display_name":"Baoyuan Wu","orcid":"https://orcid.org/0000-0003-2183-5990"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"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":"Baoyuan Wu","raw_affiliation_strings":["School of Data Science, Chinese University of Hong Kong, Shenzhen CUHK-Shenzhen) and Secure Computing Lab of Big Data, Shenzhen Research Institute of Big Data (SBRID), Shenzhen, China","School of Data Science, Chinese University of Hong Kong, Shenzhen"],"affiliations":[{"raw_affiliation_string":"School of Data Science, Chinese University of Hong Kong, Shenzhen CUHK-Shenzhen) and Secure Computing Lab of Big Data, Shenzhen Research Institute of Big Data (SBRID), Shenzhen, China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I4210116924"]},{"raw_affiliation_string":"School of Data Science, Chinese University of Hong Kong, Shenzhen","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101456902","display_name":"Chun Yuan","orcid":"https://orcid.org/0000-0002-3590-6676"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Yuan","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076879912","display_name":"Dacheng Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Dacheng Tao","raw_affiliation_strings":["College of Computing and Data Science, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"College of Computing and Data Science, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5065181430"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12706654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":"1","first_page":"436","last_page":"447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9661999940872192,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9661999940872192,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9628000259399414,"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/robustness","display_name":"Robustness (evolution)","score":0.7178999781608582},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5443999767303467},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.48570001125335693},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4652999937534332},{"id":"https://openalex.org/keywords/multiple-models","display_name":"Multiple Models","score":0.4327999949455261},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4066999852657318},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.3822000026702881},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.35899999737739563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8051999807357788},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7178999781608582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6442000269889832},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5618000030517578},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5443999767303467},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.48570001125335693},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4652999937534332},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.4327999949455261},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4066999852657318},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3822000026702881},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.35899999737739563},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3010999858379364},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3609625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3609625","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:40956731","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40956731","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1915485278","https://openalex.org/W1932198206","https://openalex.org/W2194321275","https://openalex.org/W2533598788","https://openalex.org/W2611650229","https://openalex.org/W2794825826","https://openalex.org/W2964194231","https://openalex.org/W2982802130","https://openalex.org/W3034957837","https://openalex.org/W3157466400","https://openalex.org/W3175185622","https://openalex.org/W3191459272","https://openalex.org/W3204328054","https://openalex.org/W3207659901","https://openalex.org/W3210277894","https://openalex.org/W4225963334","https://openalex.org/W4230563027","https://openalex.org/W4283816018","https://openalex.org/W4307823382","https://openalex.org/W4312585885","https://openalex.org/W4312705808","https://openalex.org/W4312908045","https://openalex.org/W4386065380","https://openalex.org/W4386071511","https://openalex.org/W4386075613","https://openalex.org/W4386075852","https://openalex.org/W4386075990","https://openalex.org/W4391164176","https://openalex.org/W4392173735","https://openalex.org/W4402592979","https://openalex.org/W4402660126","https://openalex.org/W4402917091"],"related_works":[],"abstract_inverted_index":{"Data-Free":[0],"Meta-Learning":[1],"(DFML)":[2],"aims":[3],"to":[4,35,49,98,108,126,139,184,194,199,214],"enable":[5],"efficient":[6],"learning":[7],"of":[8,41,80,112,121,232,238,246],"unseen":[9],"few-shot":[10],"tasks,":[11],"by":[12,75],"meta-learning":[13,162,222],"from":[14,32,180],"multiple":[15,181],"pre-trained":[16,130,182],"models":[17,34,135,183,219,234],"without":[18],"accessing":[19],"their":[20],"original":[21],"training":[22],"data.":[23],"While":[24],"existing":[25],"DFML":[26,154],"methods":[27],"typically":[28],"generate":[29],"synthetic":[30,159,178],"data":[31],"these":[33,148],"perform":[36,185],"meta-learning,":[37],"a":[38,118,152,192],"comprehensive":[39],"analysis":[40,56],"DFML's":[42],"robustness-particularly":[43],"its":[44,124],"failure":[45],"modes":[46],"and":[47,65,92,167],"vulnerability":[48],"potential":[50],"attacks-remains":[51],"notably":[52],"absent.":[53],"Such":[54],"an":[55,209],"is":[57],"crucial":[58],"as":[59],"algorithms":[60],"often":[61],"operate":[62],"in":[63,102,241],"complex":[64],"uncertain":[66],"real-world":[67],"environments.":[68],"This":[69],"paper":[70],"fills":[71],"this":[72],"significant":[73],"gap":[74],"systematically":[76],"investigating":[77],"the":[78,99,103,109,129,221,236,244],"robustness":[79,245],"DFML,":[81,122],"identifying":[82],"two":[83,230],"critical":[84],"but":[85,142],"previously":[86,113],"overlooked":[87],"vulnerabilities:":[88],"Task-Distribution":[89,93],"Shift":[90],"(TDS)":[91],"Corruption":[94],"(TDC).":[95],"TDS":[96],"refers":[97],"sequential":[100],"shifts":[101],"evolving":[104],"task":[105,160,164],"distribution,":[106],"leading":[107],"catastrophic":[110],"forgetting":[111],"learned":[114],"meta-knowledge.":[115,203],"TDC":[116],"exposes":[117],"security":[119],"flaw":[120],"revealing":[123],"susceptibility":[125],"attacks":[127],"when":[128],"model":[131,169,173,211],"pool":[132],"includes":[133],"untrustworthy":[134,218,233],"that":[136],"deceptively":[137],"claim":[138],"be":[140],"beneficial":[141],"are":[143],"actually":[144],"harmful.":[145],"To":[146,187],"mitigate":[147],"vulnerabilities,":[149],"we":[150,176,190],"propose":[151],"trustworthy":[153],"framework":[155,206],"comprising":[156],"three":[157],"components:":[158],"reconstruction,":[161],"with":[163,229],"memory":[165],"interpolation,":[166],"automatic":[168,210],"selection.":[170],"Specifically,":[171],"utilizing":[172],"inversion":[174],"techniques,":[175],"reconstruct":[177],"tasks":[179,198],"meta-learning.":[186],"prevent":[188],"forgetting,":[189],"introduce":[191],"strategy":[193],"replay":[195],"interpolated":[196],"historical":[197],"efficiently":[200],"recall":[201],"previous":[202],"Furthermore,":[204],"our":[205,239],"seamlessly":[207],"incorporates":[208],"selection":[212],"mechanism":[213],"automatically":[215],"filter":[216],"out":[217],"during":[220],"process.":[223],"Extensive":[224],"experiments":[225],"across":[226],"various":[227],"datasets":[228],"types":[231],"confirm":[235],"superiority":[237],"method":[240],"significantly":[242],"enhancing":[243],"DFML.":[247]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}