{"id":"https://openalex.org/W4393906128","doi":"https://doi.org/10.1109/tnnls.2024.3382724","title":"LRNAS: Differentiable Searching for Adversarially Robust Lightweight Neural Architecture","display_name":"LRNAS: Differentiable Searching for Adversarially Robust Lightweight Neural Architecture","publication_year":2024,"publication_date":"2024-04-03","ids":{"openalex":"https://openalex.org/W4393906128","doi":"https://doi.org/10.1109/tnnls.2024.3382724","pmid":"https://pubmed.ncbi.nlm.nih.gov/38568761"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3382724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3382724","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","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/A5101744703","display_name":"Yuqi Feng","orcid":"https://orcid.org/0009-0003-6264-7184"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuqi Feng","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069754254","display_name":"Zeqiong Lv","orcid":"https://orcid.org/0000-0002-1276-6711"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeqiong Lv","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008473103","display_name":"Hongyang Chen","orcid":"https://orcid.org/0000-0002-7626-0162"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyang Chen","raw_affiliation_strings":["Research Center for Graph Computing, Zhejiang Laboratory, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Research Center for Graph Computing, Zhejiang Laboratory, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010245958","display_name":"Shangce Gao","orcid":"https://orcid.org/0000-0001-5042-3261"},"institutions":[{"id":"https://openalex.org/I42766147","display_name":"University of Toyama","ror":"https://ror.org/0445phv87","country_code":"JP","type":"education","lineage":["https://openalex.org/I42766147"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shangce Gao","raw_affiliation_strings":["Faculty of Engineering, University of Toyama, Toyama, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Toyama, Toyama, Japan","institution_ids":["https://openalex.org/I42766147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016909719","display_name":"Fengping An","orcid":"https://orcid.org/0000-0002-2220-2987"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengping An","raw_affiliation_strings":["School of Automation and Software Engineering, Shanxi University, Taiyuan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and Software Engineering, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091058342","display_name":"Yanan Sun","orcid":"https://orcid.org/0000-0001-6374-1429"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanan Sun","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101744703"],"corresponding_institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"],"apc_list":null,"apc_paid":null,"fwci":2.9096,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91554492,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"36","issue":"3","first_page":"5629","last_page":"5643"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9940000176429749,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9815999865531921,"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":0.8030290603637695},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7725728750228882},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6230299472808838},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5364931225776672},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5320452451705933},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4869779050350189},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48214074969291687},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.441927969455719}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8030290603637695},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7725728750228882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6230299472808838},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5364931225776672},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5320452451705933},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4869779050350189},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48214074969291687},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.441927969455719},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3382724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3382724","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38568761","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38568761","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4607961091","display_name":null,"funder_award_id":"62271452","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G524008204","display_name":null,"funder_award_id":"62276175","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6984480226","display_name":null,"funder_award_id":"62375102","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1603628370","https://openalex.org/W2075302537","https://openalex.org/W2106875648","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2487898712","https://openalex.org/W2551176409","https://openalex.org/W2883780447","https://openalex.org/W2887063112","https://openalex.org/W2919115771","https://openalex.org/W2963163009","https://openalex.org/W2963178695","https://openalex.org/W2963446712","https://openalex.org/W2963857521","https://openalex.org/W2979503749","https://openalex.org/W2981748264","https://openalex.org/W2998279441","https://openalex.org/W3009751875","https://openalex.org/W3035467354","https://openalex.org/W3048300167","https://openalex.org/W3081624383","https://openalex.org/W3096533519","https://openalex.org/W3110617944","https://openalex.org/W3118608800","https://openalex.org/W3136450870","https://openalex.org/W3144480363","https://openalex.org/W3161934206","https://openalex.org/W3174346308","https://openalex.org/W3182590016","https://openalex.org/W3190601614","https://openalex.org/W3192682950","https://openalex.org/W3198356970","https://openalex.org/W3212436340","https://openalex.org/W4200498145","https://openalex.org/W4282937133","https://openalex.org/W4283030109","https://openalex.org/W4292828894","https://openalex.org/W4306247941","https://openalex.org/W4312633378","https://openalex.org/W4313055538","https://openalex.org/W4313130032","https://openalex.org/W4319300885","https://openalex.org/W4360798603","https://openalex.org/W4382467140","https://openalex.org/W4383955724","https://openalex.org/W6637373629","https://openalex.org/W6640425456","https://openalex.org/W6703116779","https://openalex.org/W6729956949","https://openalex.org/W6734593296","https://openalex.org/W6737947904","https://openalex.org/W6739868092","https://openalex.org/W6743495212","https://openalex.org/W6752515464","https://openalex.org/W6754642193","https://openalex.org/W6757204547","https://openalex.org/W6759129252","https://openalex.org/W6771784742","https://openalex.org/W6771809012","https://openalex.org/W6771859737","https://openalex.org/W6774451759","https://openalex.org/W6774469542","https://openalex.org/W6774575851","https://openalex.org/W6782781826","https://openalex.org/W6783646676","https://openalex.org/W6788673338","https://openalex.org/W6792722729","https://openalex.org/W6796334829","https://openalex.org/W6800107806"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"The":[0,169],"adversarial":[1,16,40,145,194],"robustness":[2,17,146],"is":[3,178],"critical":[4],"to":[5,27,72,88,133,151],"deep":[6],"neural":[7,48,67,79,183],"networks":[8],"(DNNs)":[9],"in":[10,94,136,211,217],"deployment.":[11],"However,":[12,42],"the":[13,22,34,92,95,101,124,138,140,144,152,164,167,174,204,207,214,220],"improvement":[14],"of":[15,36,91,166,206],"often":[18],"requires":[19],"compromising":[20],"with":[21,55],"network":[23],"size.":[24],"Existing":[25],"approaches":[26],"addressing":[28],"this":[29,59],"problem":[30],"mainly":[31],"focus":[32],"on":[33,47,99,117,159],"combination":[35],"model":[37,125],"compression":[38],"and":[39,65,143,189,213],"training.":[41],"their":[43],"performance":[44],"heavily":[45],"relies":[46],"architectures,":[49],"which":[50,100,121,202],"are":[51,186,199],"typically":[52],"manual":[53],"designs":[54,135],"extensive":[56,157],"expertise.":[57],"In":[58,107],"article,":[60],"we":[61,82,109],"propose":[62,83,111],"a":[63,84,118],"lightweight":[64,78,182],"robust":[66,77,191],"architecture":[68,113],"search":[69,74,86,96],"(LRNAS)":[70],"method":[71,115,177],"automatically":[73],"for":[75],"adversarially":[76,190],"architectures.":[80,154],"Specifically,":[81],"novel":[85],"strategy":[87],"quantify":[89],"contributions":[90],"components":[93,103,209],"space,":[97],"based":[98,116],"beneficial":[102,130],"can":[104,122,147],"be":[105,148],"determined.":[106],"addition,":[108],"further":[110],"an":[112],"selection":[114],"greedy":[119],"strategy,":[120],"keep":[123],"size":[126],"while":[127],"deriving":[128],"sufficient":[129],"components.":[131],"Owing":[132],"these":[134],"LRNAS,":[137],"lightness,":[139],"natural":[141],"accuracy,":[142],"collectively":[149],"guaranteed":[150],"searched":[153],"We":[155],"conduct":[156],"experiments":[158],"various":[160],"benchmark":[161],"datasets":[162],"against":[163],"state":[165],"arts.":[168],"experimental":[170],"results":[171],"demonstrate":[172],"that":[173,185],"proposed":[175],"LRNAS":[176,212],"superior":[179],"at":[180],"finding":[181],"architectures":[184],"both":[187],"accurate":[188],"under":[192],"popular":[193],"attacks.":[195],"Moreover,":[196],"ablation":[197],"studies":[198],"also":[200],"performed,":[201],"reveals":[203],"validity":[205],"individual":[208],"designed":[210],"component":[215],"effects":[216],"positively":[218],"deciding":[219],"overall":[221],"performance.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}