{"id":"https://openalex.org/W7147370594","doi":"https://doi.org/10.48550/arxiv.2603.28466","title":"Post-hoc Self-explanation of CNNs","display_name":"Post-hoc Self-explanation of CNNs","publication_year":2026,"publication_date":"2026-03-30","ids":{"openalex":"https://openalex.org/W7147370594","doi":"https://doi.org/10.48550/arxiv.2603.28466"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.28466","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.28466","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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.28466","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058501833","display_name":"Ahc\u00e8ne Boubekki","orcid":"https://orcid.org/0000-0003-1606-1513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boubekki, Ahc\u00e8ne","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5126381683","display_name":"Line Harder Clemmensen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Clemmensen, Line H.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9674000144004822,"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":0.9674000144004822,"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":0.0038999998942017555,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.0034000000450760126,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6926000118255615},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6424999833106995},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6065999865531921},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5587999820709229},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4498000144958496},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.43849998712539673},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3610999882221222},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.3179999887943268}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6926000118255615},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6797999739646912},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6467000246047974},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6424999833106995},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6065999865531921},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5587999820709229},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4498000144958496},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.43849998712539673},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2897999882698059},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.27639999985694885},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C175652121","wikidata":"https://www.wikidata.org/wiki/Q4379351","display_name":"Causal consistency","level":5,"score":0.27390000224113464},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.25859999656677246}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.28466","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.28466","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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.28466","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.28466","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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Although":[0],"standard":[1],"Convolutional":[2],"Neural":[3],"Networks":[4],"(CNNs)":[5],"can":[6],"be":[7],"mathematically":[8],"reinterpreted":[9],"as":[10,103],"Self-Explainable":[11],"Models":[12],"(SEMs),":[13],"their":[14,20],"built-in":[15],"prototypes":[16],"do":[17],"not":[18],"on":[19],"own":[21],"accurately":[22],"represent":[23],"the":[24,27,52,54,69,106],"data.":[25],"Replacing":[26],"final":[28,56],"linear":[29],"layer":[30],"with":[31,91],"a":[32,44,92,113,119],"$k$-means-based":[33,48],"classifier":[34],"addresses":[35],"this":[36],"limitation":[37],"without":[38],"compromising":[39],"performance.":[40,124],"This":[41],"work":[42],"introduces":[43],"common":[45],"formalization":[46],"of":[47,61,72],"post-hoc":[49],"explanations":[50],"for":[51],"classifier,":[53],"encoder's":[55],"output":[57],"(B4),":[58],"and":[59,118],"combinations":[60],"intermediate":[62],"feature":[63,86,100],"activations.":[64],"The":[65],"latter":[66],"approach":[67],"leverages":[68],"spatial":[70],"consistency":[71],"convolutional":[73],"receptive":[74],"fields":[75],"to":[76],"generate":[77],"concept-based":[78],"explanation":[79],"maps,":[80],"which":[81],"are":[82],"supported":[83],"by":[84],"gradient-free":[85],"attribution":[87],"maps.":[88],"Empirical":[89],"evaluation":[90],"ResNet34":[93],"shows":[94],"that":[95],"using":[96],"shallower,":[97],"less":[98],"compressed":[99],"activations,":[101],"such":[102],"those":[104],"from":[105],"last":[107],"three":[108],"blocks":[109],"(B234),":[110],"results":[111],"in":[112,122],"trade-off":[114],"between":[115],"semantic":[116],"fidelity":[117],"slight":[120],"reduction":[121],"predictive":[123]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-02T00:00:00"}