{"id":"https://openalex.org/W2945295328","doi":"https://doi.org/10.1145/3351095.3372850","title":"Explaining machine learning classifiers through diverse counterfactual explanations","display_name":"Explaining machine learning classifiers through diverse counterfactual explanations","publication_year":2020,"publication_date":"2020-01-22","ids":{"openalex":"https://openalex.org/W2945295328","doi":"https://doi.org/10.1145/3351095.3372850","mag":"2945295328"},"language":"en","primary_location":{"id":"doi:10.1145/3351095.3372850","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3351095.3372850","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3351095.3372850","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3351095.3372850","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029382491","display_name":"Ramaravind Kommiya Mothilal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Ramaravind K. Mothilal","raw_affiliation_strings":["Microsoft Research India"],"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103213915","display_name":"Amit Sharma","orcid":"https://orcid.org/0000-0002-2086-3191"},"institutions":[{"id":"https://openalex.org/I4210124949","display_name":"Microsoft Research (India)","ror":"https://ror.org/02w7f3w92","country_code":"IN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210124949"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amit Sharma","raw_affiliation_strings":["Microsoft Research India"],"affiliations":[{"raw_affiliation_string":"Microsoft Research India","institution_ids":["https://openalex.org/I4210124949"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079270249","display_name":"Chenhao Tan","orcid":"https://orcid.org/0000-0002-3981-2116"},"institutions":[{"id":"https://openalex.org/I2802236040","display_name":"University of Colorado System","ror":"https://ror.org/00jc20583","country_code":"US","type":"education","lineage":["https://openalex.org/I2802236040"]},{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenhao Tan","raw_affiliation_strings":["University of Colorado Boulder"],"affiliations":[{"raw_affiliation_string":"University of Colorado Boulder","institution_ids":["https://openalex.org/I2802236040","https://openalex.org/I188538660"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5029382491"],"corresponding_institution_ids":["https://openalex.org/I4210124949"],"apc_list":null,"apc_paid":null,"fwci":75.5717,"has_fulltext":true,"cited_by_count":1017,"citation_normalized_percentile":{"value":0.9994639,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"607","last_page":"617"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9998000264167786,"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":0.9998000264167786,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9869999885559082,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9861999750137329,"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-conditional","display_name":"Counterfactual conditional","score":0.9765543937683105},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9676293730735779},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7443795204162598},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6163747310638428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.596388578414917},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5789132118225098},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5621830821037292},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5036627650260925},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4579410254955292},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3361012041568756},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17082223296165466},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13746854662895203},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.08423057198524475}],"concepts":[{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.9765543937683105},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9676293730735779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7443795204162598},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6163747310638428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.596388578414917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5789132118225098},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5621830821037292},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5036627650260925},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4579410254955292},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3361012041568756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17082223296165466},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13746854662895203},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.08423057198524475},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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":2,"locations":[{"id":"doi:10.1145/3351095.3372850","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3351095.3372850","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3351095.3372850","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1905.07697","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.07697","pdf_url":"https://arxiv.org/pdf/1905.07697","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":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3351095.3372850","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3351095.3372850","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3351095.3372850","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G253197244","display_name":"AI-DCL: EAGER: Explanations through Diverse, Feasible, and Interactive Counterfactuals","funder_award_id":"1927322","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3865872136","display_name":null,"funder_award_id":"IIS-1927322","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2945295328.pdf","grobid_xml":"https://content.openalex.org/works/W2945295328.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1591621635","https://openalex.org/W1849277567","https://openalex.org/W1915485278","https://openalex.org/W1996796871","https://openalex.org/W2046945713","https://openalex.org/W2048089934","https://openalex.org/W2113882472","https://openalex.org/W2121368041","https://openalex.org/W2130647897","https://openalex.org/W2138216384","https://openalex.org/W2138779671","https://openalex.org/W2139590055","https://openalex.org/W2143891888","https://openalex.org/W2149033360","https://openalex.org/W2150148859","https://openalex.org/W2155912844","https://openalex.org/W2161945087","https://openalex.org/W2167162101","https://openalex.org/W2177382657","https://openalex.org/W2282821441","https://openalex.org/W2293353946","https://openalex.org/W2367397349","https://openalex.org/W2439568532","https://openalex.org/W2516809705","https://openalex.org/W2551974706","https://openalex.org/W2584924584","https://openalex.org/W2586601519","https://openalex.org/W2594475271","https://openalex.org/W2753845591","https://openalex.org/W2776186796","https://openalex.org/W2785011159","https://openalex.org/W2793566095","https://openalex.org/W2803532212","https://openalex.org/W2809002738","https://openalex.org/W2895739182","https://openalex.org/W2909392392","https://openalex.org/W2962790223","https://openalex.org/W2962862931","https://openalex.org/W2963125461","https://openalex.org/W2964121744","https://openalex.org/W2979850563","https://openalex.org/W3103014337","https://openalex.org/W3120740533","https://openalex.org/W3123671606","https://openalex.org/W4293153764","https://openalex.org/W4293583991"],"related_works":["https://openalex.org/W2056582926","https://openalex.org/W3137864021","https://openalex.org/W2162910442","https://openalex.org/W2079879923","https://openalex.org/W4200271736","https://openalex.org/W3017854570","https://openalex.org/W2104420793","https://openalex.org/W2028689793","https://openalex.org/W4313936361","https://openalex.org/W4242448314"],"abstract_inverted_index":{"Post-hoc":[0],"explanations":[1,21,41,78],"of":[2,20,47,76,88,96,132,154],"machine":[3],"learning":[4],"models":[5],"are":[6,135],"crucial":[7],"for":[8,69,116],"people":[9,29],"to":[10,31,99,111,146],"understand":[11],"and":[12,54,56,71,109,137],"act":[13],"on":[14,80,120],"algorithmic":[15],"predictions.":[16],"An":[17],"intriguing":[18],"class":[19],"is":[22],"through":[23],"counterfactuals,":[24,89],"hypothetical":[25],"examples":[26],"that":[27,38,93,125,134],"show":[28,124],"how":[30],"obtain":[32],"a":[33,67,73,130],"different":[34],"prediction.":[35],"We":[36,104,150],"posit":[37],"effective":[39],"counterfactual":[40,49,77],"should":[42],"satisfy":[43],"two":[44],"properties:":[45],"feasibility":[46],"the":[48,59,86,155],"actions":[50],"given":[51],"user":[52],"context":[53],"constraints,":[55],"diversity":[57],"among":[58],"counterfactuals":[60,133],"presented.":[61],"To":[62,84],"this":[63],"end,":[64],"we":[65,90],"propose":[66],"framework":[68,127,156],"generating":[70,147],"evaluating":[72],"diverse":[74,136,148],"set":[75,131],"based":[79],"determinantal":[81],"point":[82,110],"processes.":[83],"evaluate":[85],"actionability":[87],"provide":[91,151],"metrics":[92],"enable":[94],"comparison":[95],"counterfactual-based":[97],"methods":[98],"other":[100],"local":[101,140],"explanation":[102],"methods.":[103],"further":[105],"address":[106],"necessary":[107],"tradeoffs":[108],"causal":[112],"implications":[113],"in":[114],"optimizing":[115],"counterfactuals.":[117,149],"Our":[118],"experiments":[119],"four":[121],"real-world":[122],"datasets":[123],"our":[126],"can":[128],"generate":[129],"well":[138],"approximate":[139],"decision":[141],"boundaries,":[142],"outperforming":[143],"prior":[144],"approaches":[145],"an":[152],"implementation":[153],"at":[157],"https://github.com/microsoft/DiCE.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":38},{"year":2025,"cited_by_count":224},{"year":2024,"cited_by_count":193},{"year":2023,"cited_by_count":208},{"year":2022,"cited_by_count":147},{"year":2021,"cited_by_count":136},{"year":2020,"cited_by_count":65},{"year":2019,"cited_by_count":6}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2019-05-29T00:00:00"}