{"id":"https://openalex.org/W4402352843","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651480","title":"LoFT: LoRA-Based Efficient and Robust Fine-Tuning Framework for Adversarial Training","display_name":"LoFT: LoRA-Based Efficient and Robust Fine-Tuning Framework for Adversarial Training","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352843","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651480"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101235041","display_name":"Jiadong Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiadong Fu","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101605781","display_name":"Fang Jiang","orcid":"https://orcid.org/0000-0003-1084-5253"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang Fang","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089769533","display_name":"Jiyan Sun","orcid":"https://orcid.org/0000-0002-8479-333X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiyan Sun","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085138795","display_name":"Shangyuan Zhuang","orcid":"https://orcid.org/0000-0003-4978-9172"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangyuan Zhuang","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018053243","display_name":"Liru Geng","orcid":"https://orcid.org/0009-0008-9196-4927"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liru Geng","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013630392","display_name":"Yinlong Liu","orcid":"https://orcid.org/0000-0002-6468-8233"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinlong Liu","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Information Engineering,Beijing,China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]}],"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":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9968000054359436,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9739000201225281,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8582006096839905},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6920934915542603},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6745659112930298},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4216604232788086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3895610570907593}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8582006096839905},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6920934915542603},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6745659112930298},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4216604232788086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3895610570907593},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","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":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1945616565","https://openalex.org/W2293332611","https://openalex.org/W2788388592","https://openalex.org/W2896457183","https://openalex.org/W2908442265","https://openalex.org/W2962700793","https://openalex.org/W2962934715","https://openalex.org/W2963542245","https://openalex.org/W2990138404","https://openalex.org/W3021542222","https://openalex.org/W3023371261","https://openalex.org/W3034318565","https://openalex.org/W3035524453","https://openalex.org/W3035743198","https://openalex.org/W3096655658","https://openalex.org/W3097455551","https://openalex.org/W3168867926","https://openalex.org/W3171007011","https://openalex.org/W3176276772","https://openalex.org/W3188717957","https://openalex.org/W3190041646","https://openalex.org/W3191453585","https://openalex.org/W4221114735","https://openalex.org/W4288350321","https://openalex.org/W4288363925","https://openalex.org/W4293846201","https://openalex.org/W4307010179","https://openalex.org/W4312563846","https://openalex.org/W4322718191","https://openalex.org/W4323066824","https://openalex.org/W4362515116","https://openalex.org/W4367000428","https://openalex.org/W4367595583","https://openalex.org/W4386065392","https://openalex.org/W4387355908","https://openalex.org/W4387635340","https://openalex.org/W4390873065","https://openalex.org/W6758930985","https://openalex.org/W6759129252","https://openalex.org/W6761100157","https://openalex.org/W6774314701","https://openalex.org/W6774469542","https://openalex.org/W6779630795","https://openalex.org/W6785039685","https://openalex.org/W6788652251","https://openalex.org/W6796581206","https://openalex.org/W6803435029","https://openalex.org/W6846558609","https://openalex.org/W6849847690"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","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"],"abstract_inverted_index":{"Recently,":[0],"Self-Supervised":[1],"Learning":[2],"(SSL)":[3],"has":[4],"achieved":[5],"great":[6],"success":[7],"in":[8,80,114,143,149,175],"various":[9],"famous":[10,93],"applications":[11],"e.g.,":[12],"BERT":[13],"and":[14,37,156,203,237],"ChatGPT.":[15],"However,":[16,62],"when":[17],"applying":[18],"SSL":[19,130],"to":[20,40,55,91,163],"safety-critical":[21],"downstream":[22],"tasks,":[23],"such":[24],"as":[25],"self-driving":[26],"cars,":[27],"potential":[28],"adversarial":[29,51,58,78,102,141,161],"attacks":[30],"can":[31],"completely":[32],"change":[33],"the":[34,57,72,88,92,115,119,144,150,165,194,197,217,243],"final":[35],"decisions":[36],"thus":[38],"lead":[39],"serious":[41],"security":[42],"issues.":[43],"To":[44],"overcome":[45],"this":[46],"issue,":[47],"existing":[48,224],"methods":[49,85,104,228],"combine":[50],"training":[52,79,103,142,162,212],"with":[53,223],"pre-training":[54,81,151,202,227],"improve":[56],"robustness":[59,238],"of":[60,100,187,193,196],"SSL.":[61],"combining":[63],"these":[64],"two":[65],"computationally":[66],"complex":[67],"processes":[68],"may":[69,86],"largely":[70],"amplify":[71],"computation":[73,98],"cost.":[74],"Moreover,":[75],"whether":[76],"performing":[77],"or":[82],"fine-tuning,":[83],"current":[84,101,218],"degrade":[87],"accuracy":[89,233],"due":[90],"catastrophic":[94,166],"forgetting":[95,167],"problem.":[96,168],"The":[97,200],"cost":[99],"based":[105,131],"on":[106,132,242],"full":[107],"parameter":[108],"updating":[109,182],"is":[110],"still":[111],"high":[112],"even":[113],"fine-tuning":[116,127,145,180,204],"stage.To":[117],"address":[118],"above":[120],"challenges,":[121],"we":[122],"propose":[123],"an":[124],"effective":[125],"robust":[126,226],"framework":[128],"for":[129,229],"Low-Rank":[133],"Adaptation":[134],"(LoRA),":[135],"named":[136],"LoFT.":[137],"First,":[138],"LoFT":[139,154,170,231],"performs":[140],"stage":[146],"rather":[147],"than":[148],"stage.":[152],"Second,":[153],"innovatively":[155],"elaborately":[157],"integrates":[158],"LoRA":[159,176],"into":[160],"avoid":[164],"Third,":[169],"exploits":[171],"a":[172,184],"low-rank":[173],"matrix":[174],"which":[177,189,210],"enables":[178],"efficient":[179],"by":[181,214,234,239],"only":[183,191,207],"small":[185],"set":[186],"parameters,":[188],"contains":[190],"1%-5%":[192],"parameters":[195],"pre-trained":[198],"model.":[199],"whole":[201],"stages":[205],"take":[206],"9.44":[208],"hours,":[209],"reduces":[211],"time":[213],"3\u00d7":[215],"over":[216],"SOTA":[219,225],"method.":[220],"Furthermore,":[221],"compared":[222],"SSL,":[230],"improves":[232],"5.97%":[235],"(77.41%\u21d283.38%)":[236],"13%":[240],"(45.04%\u21d258.44%)":[241],"CIFAR-10":[244],"dataset.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}