{"id":"https://openalex.org/W3201294522","doi":"https://doi.org/10.1109/vis49827.2021.9623271","title":"AdViCE: Aggregated Visual Counterfactual Explanations for Machine Learning Model Validation","display_name":"AdViCE: Aggregated Visual Counterfactual Explanations for Machine Learning Model Validation","publication_year":2021,"publication_date":"2021-10-01","ids":{"openalex":"https://openalex.org/W3201294522","doi":"https://doi.org/10.1109/vis49827.2021.9623271","mag":"3201294522"},"language":"en","primary_location":{"id":"doi:10.1109/vis49827.2021.9623271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vis49827.2021.9623271","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Visualization Conference (VIS)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2109.05629","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058130402","display_name":"\u00d3scar G\u00f3mez","orcid":null},"institutions":[{"id":"https://openalex.org/I120250893","display_name":"New York University Abu Dhabi","ror":"https://ror.org/00e5k0821","country_code":"AE","type":"education","lineage":["https://openalex.org/I120250893","https://openalex.org/I57206974"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Oscar Gomez","raw_affiliation_strings":["New York University Abu Dhabi, Abu Dhabi, United Arab Emirates"],"affiliations":[{"raw_affiliation_string":"New York University Abu Dhabi, Abu Dhabi, United Arab Emirates","institution_ids":["https://openalex.org/I120250893"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083613211","display_name":"Steffen Holter","orcid":"https://orcid.org/0009-0008-2935-5549"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Steffen Holter","raw_affiliation_strings":["Imperial College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101693254","display_name":"Jun Yuan","orcid":"https://orcid.org/0000-0003-1952-5221"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Yuan","raw_affiliation_strings":["New York University, New York, United States"],"affiliations":[{"raw_affiliation_string":"New York University, New York, United States","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102923390","display_name":"Enrico Bertini","orcid":"https://orcid.org/0000-0002-9932-0551"},"institutions":[{"id":"https://openalex.org/I15196421","display_name":"University of Applied Sciences and Arts of Southern Switzerland","ror":"https://ror.org/05ep8g269","country_code":"CH","type":"education","lineage":["https://openalex.org/I15196421"]},{"id":"https://openalex.org/I4210102264","display_name":"Shandong University of Political Science and Law","ror":"https://ror.org/01b2j5886","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210102264"]},{"id":"https://openalex.org/I102475099","display_name":"Sup\u00e9lec","ror":"https://ror.org/00n7gwn90","country_code":"FR","type":"education","lineage":["https://openalex.org/I102475099"]}],"countries":["CH","CN","FR"],"is_corresponding":false,"raw_author_name":"Enrico Bertini","raw_affiliation_strings":["New York University<sup>**</sup>"],"affiliations":[{"raw_affiliation_string":"New York University<sup>**</sup>","institution_ids":["https://openalex.org/I15196421","https://openalex.org/I4210102264","https://openalex.org/I102475099"]}]}],"institutions":[],"countries_distinct_count":6,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058130402"],"corresponding_institution_ids":["https://openalex.org/I120250893"],"apc_list":null,"apc_paid":null,"fwci":0.14110358,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55382872,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9991999864578247,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9991999864578247,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9983999729156494,"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/T13398","display_name":"Data Analysis with R","score":0.9772999882698059,"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/overfitting","display_name":"Overfitting","score":0.8323390483856201},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.8214195966720581},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8132495880126953},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7731595039367676},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.7348394393920898},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6320056319236755},{"id":"https://openalex.org/keywords/debugging","display_name":"Debugging","score":0.5973441004753113},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5481621623039246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5128912925720215},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.4864935278892517},{"id":"https://openalex.org/keywords/advice","display_name":"Advice (programming)","score":0.4714150130748749},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.466011106967926},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4262530207633972},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4257320761680603}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8323390483856201},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.8214195966720581},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8132495880126953},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7731595039367676},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.7348394393920898},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6320056319236755},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.5973441004753113},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5481621623039246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5128912925720215},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.4864935278892517},{"id":"https://openalex.org/C2779955035","wikidata":"https://www.wikidata.org/wiki/Q4686785","display_name":"Advice (programming)","level":2,"score":0.4714150130748749},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.466011106967926},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4262530207633972},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4257320761680603},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/vis49827.2021.9623271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vis49827.2021.9623271","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Visualization Conference (VIS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2109.05629","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.05629","pdf_url":"https://arxiv.org/pdf/2109.05629","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"mag:3201294522","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2109.05629","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2109.05629","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2109.05629","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2109.05629","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.05629","pdf_url":"https://arxiv.org/pdf/2109.05629","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3201294522.pdf","grobid_xml":"https://content.openalex.org/works/W3201294522.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W2113882472","https://openalex.org/W2183009633","https://openalex.org/W2282821441","https://openalex.org/W2439568532","https://openalex.org/W2594475271","https://openalex.org/W2613800022","https://openalex.org/W2762968537","https://openalex.org/W2774522520","https://openalex.org/W2788362053","https://openalex.org/W2788403449","https://openalex.org/W2803532212","https://openalex.org/W2891340972","https://openalex.org/W2891503716","https://openalex.org/W2945295328","https://openalex.org/W2956281901","https://openalex.org/W2962772482","https://openalex.org/W2962862931","https://openalex.org/W2963095307","https://openalex.org/W2963123635","https://openalex.org/W2963795072","https://openalex.org/W2964303497","https://openalex.org/W2994363832","https://openalex.org/W2995523160","https://openalex.org/W2999765337","https://openalex.org/W3009804117","https://openalex.org/W3019489177","https://openalex.org/W3074412119","https://openalex.org/W3104847483","https://openalex.org/W3122175177","https://openalex.org/W3125501814","https://openalex.org/W3128452405","https://openalex.org/W3138819813","https://openalex.org/W6608173096","https://openalex.org/W6676885637","https://openalex.org/W6718991148","https://openalex.org/W6737947904","https://openalex.org/W6745284871","https://openalex.org/W6746809271","https://openalex.org/W6751959524","https://openalex.org/W6771539043","https://openalex.org/W6782171924","https://openalex.org/W6790587931","https://openalex.org/W6927772834","https://openalex.org/W7053318634"],"related_works":["https://openalex.org/W3009804117","https://openalex.org/W3043937498","https://openalex.org/W2963795072","https://openalex.org/W3203358361","https://openalex.org/W3023478397","https://openalex.org/W3023163568","https://openalex.org/W1597964536","https://openalex.org/W3184174269","https://openalex.org/W3159177113","https://openalex.org/W1727484914","https://openalex.org/W404856347","https://openalex.org/W3044826997","https://openalex.org/W3118337609","https://openalex.org/W2970954739","https://openalex.org/W3130185945","https://openalex.org/W3091850269","https://openalex.org/W3202452289","https://openalex.org/W3100032425","https://openalex.org/W2588967392","https://openalex.org/W2971280235"],"abstract_inverted_index":{"Rapid":[0],"improvements":[1],"in":[2,79],"the":[3,13,19,32,55,102,142,150,156],"performance":[4],"of":[5,15,22,104,141,155],"machine":[6],"learning":[7],"models":[8,24],"have":[9],"pushed":[10],"them":[11],"to":[12,76,116],"forefront":[14],"data-driven":[16],"decision-making.":[17],"Meanwhile,":[18],"increased":[20],"integration":[21],"these":[23,59],"into":[25],"various":[26],"application":[27],"domains":[28],"has":[29],"further":[30],"highlighted":[31],"need":[33],"for":[34],"greater":[35],"interpretability":[36],"and":[37,46,83,113,118,152],"transparency.":[38],"To":[39],"identify":[40],"problems":[41],"such":[42],"as":[43],"bias,":[44],"overfitting,":[45],"incorrect":[47],"correlations,":[48],"data":[49,108,129],"scientists":[50],"require":[51],"tools":[52],"that":[53,74,100,124,148],"explain":[54],"mechanisms":[56],"with":[57],"which":[58],"model":[60,81,126],"decisions":[61,105],"are":[62,131],"made.":[63],"In":[64],"this":[65],"paper":[66],"we":[67],"introduce":[68],"AdViCE,":[69],"a":[70,139,145],"visual":[71,91,114],"analytics":[72],"tool":[73,143],"aims":[75],"guide":[77],"users":[78],"black-box":[80],"debugging":[82],"validation.":[84],"The":[85],"solution":[86],"rests":[87],"on":[88,106],"two":[89],"main":[90],"user":[92],"interface":[93],"innovations:":[94],"(1)":[95],"an":[96,111],"interactive":[97],"visualization":[98],"design":[99,115],"enables":[101],"comparison":[103],"user-defined":[107],"subsets;":[109],"(2)":[110],"algorithm":[112],"compute":[117],"visualize":[119],"counterfactual":[120],"explanations":[121,123],"-":[122],"depict":[125],"outcomes":[127],"when":[128],"features":[130],"perturbed":[132],"from":[133],"their":[134],"original":[135],"values.":[136],"We":[137],"provide":[138],"demonstration":[140],"through":[144],"use":[146],"case":[147],"showcases":[149],"capabilities":[151],"potential":[153],"limitations":[154],"proposed":[157],"approach.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
