{"id":"https://openalex.org/W4391753532","doi":"https://doi.org/10.1145/3645088","title":"Triangular Trade-off between Robustness, Accuracy, and Fairness in Deep Neural Networks: A Survey","display_name":"Triangular Trade-off between Robustness, Accuracy, and Fairness in Deep Neural Networks: A Survey","publication_year":2024,"publication_date":"2024-02-12","ids":{"openalex":"https://openalex.org/W4391753532","doi":"https://doi.org/10.1145/3645088"},"language":"en","primary_location":{"id":"doi:10.1145/3645088","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3645088","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3645088","source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3645088","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jingyang Li","orcid":"https://orcid.org/0000-0002-3707-4623"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyang Li","raw_affiliation_strings":["School of Software, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3707-4623","affiliations":[{"raw_affiliation_string":"School of Software, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100354142","display_name":"Guoqiang Li","orcid":"https://orcid.org/0000-0001-9005-7112"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoqiang Li","raw_affiliation_strings":["School of Software, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9005-7112","affiliations":[{"raw_affiliation_string":"School of Software, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":3.6125,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.93292035,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"57","issue":"6","first_page":"1","last_page":"40"},"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/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9864000082015991,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9606999754905701,"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":0.8704731464385986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8095340728759766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5998306274414062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5939536094665527},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5863618850708008},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5067852139472961},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4683952331542969},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4368561804294586}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8704731464385986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8095340728759766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5998306274414062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5939536094665527},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5863618850708008},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5067852139472961},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4683952331542969},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4368561804294586},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3645088","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3645088","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3645088","source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3645088","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3645088","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3645088","source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G6956063465","display_name":null,"funder_award_id":"62161146001","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"},{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"},{"id":"https://openalex.org/F4320322370","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391753532.pdf","grobid_xml":"https://content.openalex.org/works/W4391753532.grobid-xml"},"referenced_works_count":79,"referenced_works":["https://openalex.org/W1570448133","https://openalex.org/W1861492603","https://openalex.org/W1933349210","https://openalex.org/W1936750108","https://openalex.org/W1977230515","https://openalex.org/W2014352947","https://openalex.org/W2076063813","https://openalex.org/W2108598243","https://openalex.org/W2116984840","https://openalex.org/W2180612164","https://openalex.org/W2194775991","https://openalex.org/W2243397390","https://openalex.org/W2257979135","https://openalex.org/W2533641151","https://openalex.org/W2543296129","https://openalex.org/W2594877703","https://openalex.org/W2603766943","https://openalex.org/W2611576673","https://openalex.org/W2704480242","https://openalex.org/W2746600820","https://openalex.org/W2752782242","https://openalex.org/W2765982206","https://openalex.org/W2774510177","https://openalex.org/W2775261393","https://openalex.org/W2791251367","https://openalex.org/W2794609696","https://openalex.org/W2800415562","https://openalex.org/W2809878087","https://openalex.org/W2887603965","https://openalex.org/W2951476734","https://openalex.org/W2954996726","https://openalex.org/W2957311447","https://openalex.org/W2962692913","https://openalex.org/W2962718684","https://openalex.org/W2963446712","https://openalex.org/W2963457723","https://openalex.org/W2963501948","https://openalex.org/W2963857521","https://openalex.org/W2963952467","https://openalex.org/W2963998105","https://openalex.org/W2964247748","https://openalex.org/W2966658324","https://openalex.org/W2979878901","https://openalex.org/W2982540258","https://openalex.org/W2985793077","https://openalex.org/W2997352032","https://openalex.org/W2999606423","https://openalex.org/W3003768009","https://openalex.org/W3015481738","https://openalex.org/W3025991882","https://openalex.org/W3033733989","https://openalex.org/W3047533667","https://openalex.org/W3047806505","https://openalex.org/W3091896612","https://openalex.org/W3101767999","https://openalex.org/W3102092462","https://openalex.org/W3102139284","https://openalex.org/W3106412272","https://openalex.org/W3118608800","https://openalex.org/W3119150429","https://openalex.org/W3121523901","https://openalex.org/W3146796711","https://openalex.org/W3152436735","https://openalex.org/W3158363482","https://openalex.org/W3168586460","https://openalex.org/W3171889065","https://openalex.org/W3181414820","https://openalex.org/W3201862353","https://openalex.org/W3206456554","https://openalex.org/W4250998378","https://openalex.org/W4283206275","https://openalex.org/W4287693778","https://openalex.org/W4288083810","https://openalex.org/W4288319633","https://openalex.org/W4294560781","https://openalex.org/W4306412326","https://openalex.org/W6640773114","https://openalex.org/W7052973119","https://openalex.org/W7056365848"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W4383221314","https://openalex.org/W3093978547","https://openalex.org/W2953536436","https://openalex.org/W3203790781","https://openalex.org/W4313346231","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W2997056298"],"abstract_inverted_index":{"With":[0],"the":[1,20,45,53,68,188],"rapid":[2],"development":[3],"of":[4,23,67,143,147,197],"deep":[5,100],"learning,":[6],"AI":[7,85],"systems":[8,86],"are":[9,163],"being":[10],"used":[11],"more":[12,181],"in":[13,76,99,155],"complex":[14],"and":[15,18,28,74,91,97,107,115,123,126,128,130,145,169,193],"important":[16],"domains":[17],"necessitates":[19],"simultaneous":[21],"fulfillment":[22],"multiple":[24],"constraints:":[25],"accurate,":[26],"robust,":[27],"fair.":[29],"Accuracy":[30],"measures":[31],"how":[32,43],"well":[33,44],"a":[34,141],"DNN":[35],"can":[36,47],"generalize":[37],"to":[38,87,94,110,135,186],"new":[39],"data.":[40],"Robustness":[41],"demonstrates":[42],"network":[46],"withstand":[48],"minor":[49],"perturbations":[50],"without":[51],"changing":[52],"results.":[54],"Fairness":[55],"focuses":[56],"on":[57],"treating":[58],"different":[59,136],"groups":[60],"equally.":[61],"This":[62,79,183],"survey":[63,103,184],"provides":[64],"an":[65],"overview":[66],"triangular":[69],"trade-off":[70,80,152],"among":[71],"robustness,":[72,96,124],"accuracy,":[73],"fairness":[75,98,131],"neural":[77],"networks.":[78],"makes":[81],"it":[82,159],"difficult":[83],"for":[84],"achieve":[88],"true":[89],"intelligence":[90],"is":[92,140,153],"connected":[93],"generalization,":[95],"learning.":[101,118],"The":[102,119,150,167],"explores":[104],"these":[105,148,198],"trade-offs":[106,120,171],"their":[108,177],"relationships":[109],"adversarial":[111,113],"examples,":[112],"training,":[114],"fair":[116],"machine":[117],"between":[121],"accuracy":[122,125],"fairness,":[127],"robustness":[129],"have":[132,172],"been":[133,173],"studied":[134],"extents.":[137],"However,":[138],"there":[139],"lack":[142],"taxonomy":[144],"analysis":[146],"trade-offs.":[149,199],"accuracy-robustness":[151],"inherent":[154],"Gaussian":[156],"models,":[157],"but":[158,176],"varies":[160],"when":[161],"classes":[162],"not":[164],"closely":[165],"distributed.":[166],"accuracy-fairness":[168],"robustness-fairness":[170],"assessed":[174],"empirically,":[175],"theoretical":[178],"nature":[179],"needs":[180],"investigation.":[182],"aims":[185],"explore":[187],"origins,":[189],"evolution,":[190],"influencing":[191],"factors,":[192],"future":[194],"research":[195],"directions":[196]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
