{"id":"https://openalex.org/W4415324883","doi":"https://doi.org/10.1007/978-3-032-08333-3_17","title":"Explaining Low Perception Model Competency with\u00a0High-Competency Counterfactuals","display_name":"Explaining Low Perception Model Competency with\u00a0High-Competency Counterfactuals","publication_year":2025,"publication_date":"2025-10-18","ids":{"openalex":"https://openalex.org/W4415324883","doi":"https://doi.org/10.1007/978-3-032-08333-3_17"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-032-08333-3_17","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-08333-3_17","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_17.pdf","source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_17.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087146422","display_name":"Sara Pohland","orcid":"https://orcid.org/0000-0003-2746-6372"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sara Pohland","raw_affiliation_strings":["University of California, Berkeley, CA, 94720, USA"],"raw_orcid":"https://orcid.org/0000-0003-2746-6372","affiliations":[{"raw_affiliation_string":"University of California, Berkeley, CA, 94720, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045155646","display_name":"Claire J. Tomlin","orcid":"https://orcid.org/0000-0003-3192-3185"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Claire Tomlin","raw_affiliation_strings":["University of California, Berkeley, CA, 94720, USA"],"raw_orcid":"https://orcid.org/0000-0003-3192-3185","affiliations":[{"raw_affiliation_string":"University of California, Berkeley, CA, 94720, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5087146422"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25343323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"364","last_page":"389"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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":0.9962000250816345,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9940000176429749,"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":0.9273999929428101},{"id":"https://openalex.org/keywords/counterfactual-conditional","display_name":"Counterfactual conditional","score":0.7734000086784363},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6044999957084656},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.5999000072479248},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5667999982833862},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.551800012588501},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4092000126838684}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9273999929428101},{"id":"https://openalex.org/C71889745","wikidata":"https://www.wikidata.org/wiki/Q1783264","display_name":"Counterfactual conditional","level":3,"score":0.7734000086784363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6854000091552734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6190999746322632},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6044999957084656},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.5999000072479248},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5667999982833862},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.551800012588501},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5325000286102295},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4092000126838684},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.397599995136261},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3346000015735626},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.29980000853538513},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.2761000096797943},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2669000029563904}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-032-08333-3_17","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-08333-3_17","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_17.pdf","source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-3-032-08333-3_17","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-032-08333-3_17","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-032-08333-3_17.pdf","source":{"id":"https://openalex.org/S2764900261","display_name":"Communications in computer and information science","issn_l":"1865-0929","issn":["1865-0929","1865-0937"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Computer and Information Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415324883.pdf","grobid_xml":"https://content.openalex.org/works/W4415324883.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1567512734","https://openalex.org/W2002427601","https://openalex.org/W2204904589","https://openalex.org/W2895387715","https://openalex.org/W2962785568","https://openalex.org/W2963061824","https://openalex.org/W2963149653","https://openalex.org/W2973319951","https://openalex.org/W2987228832","https://openalex.org/W2998512575","https://openalex.org/W3004170979","https://openalex.org/W3016419862","https://openalex.org/W3103795814","https://openalex.org/W3126483755","https://openalex.org/W3126686938","https://openalex.org/W3152966291","https://openalex.org/W3187709298","https://openalex.org/W3214023923","https://openalex.org/W4206148563","https://openalex.org/W4212952176","https://openalex.org/W4312265095","https://openalex.org/W4312284582","https://openalex.org/W4312780623","https://openalex.org/W4366262984","https://openalex.org/W4378976798","https://openalex.org/W4386065385","https://openalex.org/W4393086018","https://openalex.org/W4400438905","https://openalex.org/W4402753378","https://openalex.org/W4403034246","https://openalex.org/W4403938790","https://openalex.org/W4405262867","https://openalex.org/W4411119927"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"There":[1],"exist":[2],"many":[3],"methods":[4,21,118,148,174,184,254],"to":[5,22,50,70,77,80,95,119,169,195,224],"explain":[6,23,60],"how":[7,181],"an":[8,78,97,226],"image":[9,79,211],"classification":[10,84],"model":[11,49,101,161,201,215,223,234,247],"generates":[12],"its":[13,31,54],"decision,":[14],"but":[15,58],"very":[16],"little":[17],"work":[18],"has":[19],"explored":[20],"why":[24,61],"a":[25,82,209],"classifier":[26,39],"might":[27,40],"lack":[28],"confidence":[29],"in":[30,212,243],"prediction.":[32],"As":[33],"there":[34],"are":[35],"various":[36],"reasons":[37],"the":[38,91,171,206,213,219,222,230,238],"lose":[41],"confidence,":[42],"it":[43,62],"would":[44],"be":[45,75,170,186],"valuable":[46],"for":[47,99,159,175,199,229,251],"this":[48,87,112],"not":[51],"only":[52],"indicate":[53],"level":[55],"of":[56,93,105,208,221,232,240],"uncertainty":[57,107],"also":[59],"is":[63,257],"uncertain.":[64],"Counterfactual":[65],"images":[66,154,242],"have":[67],"been":[68],"used":[69],"visualize":[71],"changes":[72],"that":[73,108,205],"could":[74],"made":[76],"generate":[81,120,196,225],"different":[83],"decision.":[85],"In":[86],"work,":[88],"we":[89,114],"explore":[90],"use":[92],"counterfactuals":[94],"offer":[96],"explanation":[98,228],"low":[100,160,200,233,245],"competency\u2013a":[102],"generalized":[103],"form":[104],"predictive":[106],"measures":[109],"confidence.":[110],"Toward":[111],"end,":[113],"develop":[115],"five":[116],"novel":[117],"high-competency":[121],"counterfactual":[122,176,210,241],"images,":[123],"namely":[124],"Image":[125],"Gradient":[126,130,137],"Descent":[127,131,138],"(IGD),":[128],"Feature":[129],"(FGD),":[132],"Autoencoder":[133],"Reconstruction":[134],"(Reco),":[135],"Latent":[136,141],"(LGD),":[139],"and":[140,163,167,255],"Nearest":[142],"Neighbors":[143],"(LNN).":[144],"We":[145,178,203],"evaluate":[146,180],"these":[147,182],"across":[149],"two":[150],"unique":[151],"datasets":[152],"containing":[153],"with":[155],"six":[156],"known":[157],"causes":[158],"competency":[162,248],"find":[164,204],"Reco,":[165],"LGD,":[166],"LNN":[168],"most":[172],"promising":[173],"generation.":[177],"further":[179],"three":[183],"can":[185],"utilized":[187],"by":[188],"pre-trained":[189],"Multimodal":[190],"Large":[191],"Language":[192],"Models":[193],"(MLLMs)":[194],"language":[197,214],"explanations":[198],"competency.":[202],"inclusion":[207],"query":[216],"greatly":[217],"increases":[218],"ability":[220],"accurate":[227],"cause":[231],"competency,":[235],"thus":[236],"demonstrating":[237],"utility":[239],"explaining":[244],"perception":[246],"(The":[249],"code":[250],"reproducing":[252],"our":[253],"results":[256],"available":[258],"on":[259],"GitHub:":[260],"https://github.com/sarapohland/competency-counterfactuals":[261],".).":[262]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-19T00:00:00"}
