{"id":"https://openalex.org/W4409157914","doi":"https://doi.org/10.1145/3690624.3709337","title":"Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation","display_name":"Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation","publication_year":2025,"publication_date":"2025-04-04","ids":{"openalex":"https://openalex.org/W4409157914","doi":"https://doi.org/10.1145/3690624.3709337"},"language":"en","primary_location":{"id":"doi:10.1145/3690624.3709337","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3690624.3709337","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3690624.3709337","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100341185","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0001-6135-6965"},"institutions":[{"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":true,"raw_author_name":"Qi (Cheems) Wang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055359094","display_name":"Yiqin Lv","orcid":"https://orcid.org/0000-0003-1181-0212"},"institutions":[{"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":"Yiqin Lv","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106224035","display_name":"Yixiu Mao","orcid":null},"institutions":[{"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":"Yixiu Mao","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109367087","display_name":"Yun Qu","orcid":null},"institutions":[{"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":"Yun Qu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101848163","display_name":"Yi Xu","orcid":"https://orcid.org/0009-0000-9900-6143"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Xu","raw_affiliation_strings":["Dalian University of Technology, Dalian, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Dalian University of Technology, Dalian, Liaoning, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102859000","display_name":"Xiangyang Ji","orcid":"https://orcid.org/0000-0001-9542-5260"},"institutions":[{"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":"Xiangyang Ji","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100341185"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":5.5956,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.94963121,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1481","last_page":"1491"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987999796867371,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9987999796867371,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9962999820709229,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9937999844551086,"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/computer-science","display_name":"Computer science","score":0.7007611989974976},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6828148365020752},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6822585463523865},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.38700777292251587},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09156891703605652},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0820976197719574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7007611989974976},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6828148365020752},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6822585463523865},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.38700777292251587},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09156891703605652},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0820976197719574},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3690624.3709337","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3690624.3709337","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3690624.3709337","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3690624.3709337","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1971057573","https://openalex.org/W2104906962","https://openalex.org/W2137825550","https://openalex.org/W2158782408","https://openalex.org/W2296073425","https://openalex.org/W2750779823","https://openalex.org/W2787597845","https://openalex.org/W2979689312","https://openalex.org/W2990138404","https://openalex.org/W3001176757","https://openalex.org/W3036176146","https://openalex.org/W3040863728","https://openalex.org/W3096831136","https://openalex.org/W3135126802","https://openalex.org/W3139610437","https://openalex.org/W3166286441","https://openalex.org/W3167525829","https://openalex.org/W3173280621","https://openalex.org/W3187710359","https://openalex.org/W3200043857","https://openalex.org/W3213724640","https://openalex.org/W3214138187","https://openalex.org/W3214142563","https://openalex.org/W3215641581","https://openalex.org/W4214660208","https://openalex.org/W4281399313","https://openalex.org/W4287815740","https://openalex.org/W4292025355","https://openalex.org/W4302285999","https://openalex.org/W4304479547","https://openalex.org/W4312363838","https://openalex.org/W4382246105","https://openalex.org/W4386865748","https://openalex.org/W4402753979","https://openalex.org/W6600655691","https://openalex.org/W6604377271","https://openalex.org/W6779481570","https://openalex.org/W6780171218","https://openalex.org/W6803673623","https://openalex.org/W6838607562","https://openalex.org/W6845988380"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Meta-learning":[0],"is":[1,34,150],"a":[2,12,76,79],"practical":[3,108],"learning":[4],"paradigm":[5],"to":[6,23,44,121],"transfer":[7],"skills":[8],"across":[9],"tasks":[10],"from":[11,66,90],"few":[13],"examples.":[14],"Nevertheless,":[15],"the":[16,30,85,99,125,133,153],"existence":[17],"of":[18,78,135],"task":[19,32,55,59,86,114,136],"distribution":[20,33,115],"shifts":[21,116,138],"tends":[22],"weaken":[24],"meta-learners'":[25],"generalization":[26],"capability,":[27],"particularly":[28,110],"when":[29],"training":[31],"naively":[35],"hand-crafted":[36],"or":[37],"based":[38],"on":[39],"simple":[40],"priors":[41],"that":[42],"fail":[43],"cover":[45],"critical":[46],"scenarios":[47],"sufficiently.":[48],"Here,":[49],"we":[50],"consider":[51],"explicitly":[52],"generative":[53,93],"modeling":[54],"distributions":[56],"placed":[57],"over":[58,142],"identifiers":[60],"and":[61,119,139],"propose":[62],"robustifying":[63],"fast":[64],"adaptation":[65,100],"adversarial":[67],"training.":[68],"Our":[69,127],"approach,":[70],"which":[71],"can":[72],"be":[73],"interpreted":[74],"as":[75],"model":[77,94],"Stackelberg":[80],"game,":[81],"not":[82],"only":[83],"uncovers":[84],"structure":[87],"during":[88],"problem-solving":[89],"an":[91],"explicit":[92],"but":[95],"also":[96],"theoretically":[97],"increases":[98],"robustness":[101,131],"in":[102,111,117,124,132,145],"worst":[103],"cases.":[104],"This":[105],"work":[106],"has":[107],"implications,":[109],"dealing":[112],"with":[113],"meta-learning,":[118],"contributes":[120],"theoretical":[122],"insights":[123],"field.":[126],"method":[128],"demonstrates":[129],"its":[130],"presence":[134],"subpopulation":[137],"improved":[140],"performance":[141],"SOTA":[143],"baselines":[144],"extensive":[146],"experiments.":[147],"The":[148],"code":[149],"available":[151],"at":[152],"project":[154],"site":[155],"https://sites.google.com/view/ar-metalearn.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}