{"id":"https://openalex.org/W4406400595","doi":"https://doi.org/10.1017/s1471068424000322","title":"A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks","display_name":"A Neurosymbolic Framework for Bias Correction in Convolutional Neural Networks","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4406400595","doi":"https://doi.org/10.1017/s1471068424000322"},"language":"en","primary_location":{"id":"doi:10.1017/s1471068424000322","is_oa":true,"landing_page_url":"https://doi.org/10.1017/s1471068424000322","pdf_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C0E31D22491029D95EBED338A3073518/S1471068424000322a.pdf/div-class-title-a-neurosymbolic-framework-for-bias-correction-in-convolutional-neural-networks-div.pdf","source":{"id":"https://openalex.org/S59670734","display_name":"Theory and Practice of Logic Programming","issn_l":"1471-0684","issn":["1471-0684","1475-3081"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Theory and Practice of Logic Programming","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C0E31D22491029D95EBED338A3073518/S1471068424000322a.pdf/div-class-title-a-neurosymbolic-framework-for-bias-correction-in-convolutional-neural-networks-div.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058520906","display_name":"Parth Padalkar","orcid":"https://orcid.org/0000-0003-1015-0777"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"PARTH PADALKAR","raw_affiliation_strings":["The University of Texas at Dallas, Richardson, TX, USA (e-mail:"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Dallas, Richardson, TX, USA (e-mail:","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065519694","display_name":"Natalia Slusarz","orcid":null},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"NATALIA \u015aLUSARZ","raw_affiliation_strings":["Heriot-Watt University, Edinburgh, UK (e-mail:"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University, Edinburgh, UK (e-mail:","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026643182","display_name":"Ekaterina Komendantskaya","orcid":"https://orcid.org/0000-0002-3240-0987"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"EKATERINA KOMENDANTSKAYA","raw_affiliation_strings":["Southampton University, Heriot-Watt University, Edinburgh, UK (e-mail:"],"affiliations":[{"raw_affiliation_string":"Southampton University, Heriot-Watt University, Edinburgh, UK (e-mail:","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067377863","display_name":"Gopal Gupta","orcid":"https://orcid.org/0000-0001-9727-0362"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"GOPAL GUPTA","raw_affiliation_strings":["The University of Texas at Dallas, Richardson, TX, USA (e-mail:"],"affiliations":[{"raw_affiliation_string":"The University of Texas at Dallas, Richardson, TX, USA (e-mail:","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058520906"],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":0.7024,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.77971017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"24","issue":"4","first_page":"644","last_page":"662"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.5892000198364258,"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/T10320","display_name":"Neural Networks and Applications","score":0.5892000198364258,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.5196999907493591,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.901429295539856},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7166595458984375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4700578451156616}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.901429295539856},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7166595458984375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4700578451156616}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s1471068424000322","is_oa":true,"landing_page_url":"https://doi.org/10.1017/s1471068424000322","pdf_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C0E31D22491029D95EBED338A3073518/S1471068424000322a.pdf/div-class-title-a-neurosymbolic-framework-for-bias-correction-in-convolutional-neural-networks-div.pdf","source":{"id":"https://openalex.org/S59670734","display_name":"Theory and Practice of Logic Programming","issn_l":"1471-0684","issn":["1471-0684","1475-3081"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Theory and Practice of Logic Programming","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1017/s1471068424000322","is_oa":true,"landing_page_url":"https://doi.org/10.1017/s1471068424000322","pdf_url":"https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C0E31D22491029D95EBED338A3073518/S1471068424000322a.pdf/div-class-title-a-neurosymbolic-framework-for-bias-correction-in-convolutional-neural-networks-div.pdf","source":{"id":"https://openalex.org/S59670734","display_name":"Theory and Practice of Logic Programming","issn_l":"1471-0684","issn":["1471-0684","1475-3081"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Theory and Practice of Logic Programming","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3330119427","display_name":null,"funder_award_id":"EPSRC","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5778312650","display_name":null,"funder_award_id":"EP/T026952/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5838310497","display_name":"AISEC: AI Secure and Explainable by Construction","funder_award_id":"EP/T026952/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7024220182","display_name":"RI: SMALL: Inducing Answer Set Programs to Provide Accurate and Concise Explanation of Machine-learned Models","funder_award_id":"1910131","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"},{"id":"https://openalex.org/F4320327708","display_name":"University of Texas at Dallas","ror":"https://ror.org/049emcs32"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406400595.pdf","grobid_xml":"https://content.openalex.org/works/W4406400595.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Abstract":[0],"Recent":[1],"efforts":[2],"in":[3,38,78,97,163],"interpreting":[4],"convolutional":[5],"neural":[6],"networks":[7],"(CNNs)":[8],"focus":[9],"on":[10],"translating":[11],"the":[12,36,39,44,52,55,59,62,76,82,108,115,123,135,142,153,161,164,167,177,187],"activation":[13],"of":[14,58,166,179,184],"CNN":[15,26,60,109,124],"filters":[16,27,136],"into":[17],"a":[18,85,89,98,156],"stratified":[19],"Answer":[20],"Set":[21],"Program":[22],"(ASP)":[23],"rule-sets.":[24],"The":[25,145],"are":[28,41],"known":[29],"to":[30,43,117,155],"capture":[31],"high-level":[32],"image":[33,69],"concepts,":[34,103],"thus":[35,159],"predicates":[37],"rule-set":[40,53,148],"mapped":[42],"concept":[45],"that":[46,64,107,133,171],"their":[47,118],"corresponding":[48,119],"filter":[49],"represents.":[50],"Hence,":[51],"exemplifies":[54],"decision-making":[56],"process":[57],"w.r.t":[61],"concepts":[63,116],"it":[65],"learns":[66],"for":[67,94],"any":[68],"classification":[70],"task.":[71],"These":[72],"rule-sets":[73],"help":[74],"understand":[75],"biases":[77,83,178],"CNNs,":[79],"although":[80],"correcting":[81],"remains":[84],"challenge.":[86],"We":[87,169],"introduce":[88],"neurosymbolic":[90],"framework":[91,174],"called":[92],"NeSyBiCor":[93,173],"bias":[95],"correction":[96],"trained":[99,181],"CNN.":[100,168],"Given":[101],"symbolic":[102],"as":[104],"ASP":[105,147],"constraints,":[106],"is":[110,125],"biased":[111],"toward,":[112],"we":[113],"convert":[114],"vector":[120],"representations.":[121],"Then,":[122],"retrained":[126],"using":[127],"our":[128,172],"novel":[129],"semantic":[130],"similarity":[131],"loss":[132],"pushes":[134],"away":[137],"from":[138,186],"(or":[139],"toward)":[140],"learning":[141],"desired/undesired":[143],"concepts.":[144],"final":[146],"obtained":[149],"after":[150],"retraining,":[151],"satisfies":[152],"constraints":[154],"high":[157],"degree,":[158],"showing":[160],"revision":[162],"knowledge":[165],"demonstrate":[170],"successfully":[175],"corrects":[176],"CNNs":[180],"with":[182],"subsets":[183],"classes":[185],"Places":[188],"dataset":[189],"while":[190],"sacrificing":[191],"minimal":[192],"accuracy":[193],"and":[194],"improving":[195],"interpretability.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-10T00:00:00"}
