{"id":"https://openalex.org/W4390661547","doi":"https://doi.org/10.1007/s43681-023-00407-0","title":"Assessing systematic weaknesses of DNNs using counterfactuals","display_name":"Assessing systematic weaknesses of DNNs using counterfactuals","publication_year":2024,"publication_date":"2024-01-08","ids":{"openalex":"https://openalex.org/W4390661547","doi":"https://doi.org/10.1007/s43681-023-00407-0"},"language":"en","primary_location":{"id":"doi:10.1007/s43681-023-00407-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s43681-023-00407-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s43681-023-00407-0.pdf","source":{"id":"https://openalex.org/S4210170699","display_name":"AI and Ethics","issn_l":"2730-5953","issn":["2730-5953","2730-5961"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI and Ethics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s43681-023-00407-0.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020613750","display_name":"Sujan Sai Gannamaneni","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Sujan Sai Gannamaneni","raw_affiliation_strings":["Fraunhofer IAIS, Sankt Augustin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer IAIS, Sankt Augustin, Germany","institution_ids":["https://openalex.org/I4210144576"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062749833","display_name":"Michael M\u00f6ck","orcid":"https://orcid.org/0009-0009-9864-8924"},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Mock","raw_affiliation_strings":["Fraunhofer IAIS, Sankt Augustin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer IAIS, Sankt Augustin, Germany","institution_ids":["https://openalex.org/I4210144576"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103922413","display_name":"Maram Akila","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maram Akila","raw_affiliation_strings":["Fraunhofer IAIS, Sankt Augustin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer IAIS, Sankt Augustin, Germany","institution_ids":["https://openalex.org/I4210144576"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5020613750"],"corresponding_institution_ids":["https://openalex.org/I4210144576"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":0.9441,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77231363,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"4","issue":"1","first_page":"27","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9990000128746033,"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":0.9990000128746033,"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/T11357","display_name":"Risk and Safety Analysis","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.986299991607666,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.7912701368331909},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7436257004737854},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6183646321296692},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.5945659875869751},{"id":"https://openalex.org/keywords/counterfactual-conditional","display_name":"Counterfactual conditional","score":0.593926727771759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4696834683418274},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4527953863143921},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.434799462556839},{"id":"https://openalex.org/keywords/asset","display_name":"Asset (computer security)","score":0.42053475975990295},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4171485900878906},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3877168297767639},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3208310902118683},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1169421374797821},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08345767855644226}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.7912701368331909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7436257004737854},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6183646321296692},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.5945659875869751},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.593926727771759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4696834683418274},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4527953863143921},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.434799462556839},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.42053475975990295},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4171485900878906},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3877168297767639},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3208310902118683},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1169421374797821},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08345767855644226},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s43681-023-00407-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s43681-023-00407-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s43681-023-00407-0.pdf","source":{"id":"https://openalex.org/S4210170699","display_name":"AI and Ethics","issn_l":"2730-5953","issn":["2730-5953","2730-5961"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI and Ethics","raw_type":"journal-article"},{"id":"pmh:oai:publica.fraunhofer.de:publica/481668","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/481668","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.1007/s43681-023-00407-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s43681-023-00407-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s43681-023-00407-0.pdf","source":{"id":"https://openalex.org/S4210170699","display_name":"AI and Ethics","issn_l":"2730-5953","issn":["2730-5953","2730-5961"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI and Ethics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390661547.pdf"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2055400097","https://openalex.org/W2282821441","https://openalex.org/W2338621248","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2786808285","https://openalex.org/W2884061367","https://openalex.org/W2891340972","https://openalex.org/W2892220819","https://openalex.org/W2917286209","https://openalex.org/W2945295328","https://openalex.org/W2947263797","https://openalex.org/W2962700793","https://openalex.org/W3019132020","https://openalex.org/W3034697737","https://openalex.org/W3034700241","https://openalex.org/W3099331386","https://openalex.org/W3101038122","https://openalex.org/W3104149808","https://openalex.org/W3110687307","https://openalex.org/W3135367836","https://openalex.org/W3135487809","https://openalex.org/W3173326111","https://openalex.org/W3176345100","https://openalex.org/W3182543254","https://openalex.org/W3209443656","https://openalex.org/W4285172631","https://openalex.org/W6602390520","https://openalex.org/W6605919414","https://openalex.org/W6753134527"],"related_works":["https://openalex.org/W2056582926","https://openalex.org/W3137864021","https://openalex.org/W4200271736","https://openalex.org/W2079879923","https://openalex.org/W2162910442","https://openalex.org/W2104420793","https://openalex.org/W3017854570","https://openalex.org/W2028689793","https://openalex.org/W4242448314","https://openalex.org/W3028884462"],"abstract_inverted_index":{"Abstract":[0],"With":[1],"the":[2,22,46,55,74,82,88,94,132,142,150,161,183,195,199,205],"advancement":[3],"of":[4,27,48,135],"DNNs":[5],"into":[6,105],"safety-critical":[7],"applications,":[8],"testing":[9],"approaches":[10],"for":[11,24,76,173,201],"such":[12,77],"models":[13],"have":[14,148],"gained":[15],"more":[16],"attention.":[17],"A":[18],"current":[19],"direction":[20],"is":[21,70,113,145,194],"search":[23],"and":[25,110,126],"identification":[26],"systematic":[28],"weaknesses":[29,42],"that":[30,86,178],"put":[31],"safety":[32],"assumptions":[33],"based":[34],"on":[35,45,157],"average":[36],"performance":[37,180],"values":[38],"at":[39],"risk.":[40],"Such":[41],"can":[43],"take":[44],"form":[47],"(semantically":[49],"coherent)":[50],"subsets":[51],"or":[52],"areas":[53],"in":[54,191,204],"input":[56],"space":[57],"where":[58,170],"a":[59,174],"DNN":[60],"performs":[61],"systematically":[62],"worse":[63],"than":[64],"its":[65],"expected":[66],"average.":[67],"However,":[68,103],"it":[69],"non-trivial":[71],"to":[72,81,130,139,147],"attribute":[73,144],"reason":[75,200],"observed":[78],"low":[79],"performances":[80],"specific":[83],"semantic":[84,133,175],"features":[85],"describe":[87],"subset.":[89],"For":[90],"instance,":[91],"inhomogeneities":[92],"within":[93],"data":[95],"w.r.t.":[96],"other":[97],"(non-considered)":[98],"attributes":[99,109],"might":[100],"distort":[101],"results.":[102],"taking":[104],"account":[106],"all":[107],"(available)":[108],"their":[111],"interaction":[112],"often":[114],"computationally":[115,127],"highly":[116,166],"expensive.":[117],"Inspired":[118],"by":[119],"counterfactual":[120],"explanations,":[121],"we":[122,171],"propose":[123],"an":[124,158],"effective":[125],"cheap":[128],"algorithm":[129],"validate":[131],"attribution":[134],"existing":[136],"subsets,":[137],"i.e.,":[138],"check":[140],"whether":[141],"identified":[143],"likely":[146],"caused":[149],"degraded":[151],"performance.":[152,206],"We":[153],"demonstrate":[154],"this":[155,202],"approach":[156],"example":[159],"from":[160],"autonomous":[162],"driving":[163],"domain":[164],"using":[165],"annotated":[167],"simulated":[168],"data,":[169],"show":[172],"segmentation":[176],"model":[177],"(i)":[179],"differences":[181],"among":[182],"different":[184],"pedestrian":[185],"assets":[186],"exist,":[187],"but":[188],"(ii)":[189],"only":[190],"some":[192],"cases":[193],"asset":[196],"type":[197],"itself":[198],"reduction":[203]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}