{"id":"https://openalex.org/W7138369647","doi":"https://doi.org/10.1609/aaai.v40i6.42424","title":"Concepts from Representations: Post-hoc Concept Bottleneck Models via Sparse Decomposition of Visual Representations","display_name":"Concepts from Representations: Post-hoc Concept Bottleneck Models via Sparse Decomposition of Visual Representations","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138369647","doi":"https://doi.org/10.1609/aaai.v40i6.42424"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i6.42424","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42424","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i6.42424","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056031374","display_name":"Shizhan Gong","orcid":"https://orcid.org/0009-0002-0056-9611"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shizhan Gong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129713210","display_name":"Xiaofan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaofan Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129719039","display_name":"Qi Dou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Dou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"6","first_page":"4275","last_page":"4283"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4659000039100647,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.4659000039100647,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.23280000686645508,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0917000025510788,"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/interpretability","display_name":"Interpretability","score":0.8363999724388123},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7932999730110168},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5482000112533569},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5008999705314636},{"id":"https://openalex.org/keywords/rotation-formalisms-in-three-dimensions","display_name":"Rotation formalisms in three dimensions","score":0.48890000581741333},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4832000136375427},{"id":"https://openalex.org/keywords/identifiability","display_name":"Identifiability","score":0.46140000224113464},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45750001072883606},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4404999911785126}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8363999724388123},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7932999730110168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7231000065803528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6696000099182129},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5482000112533569},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5192999839782715},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5008999705314636},{"id":"https://openalex.org/C171018156","wikidata":"https://www.wikidata.org/wiki/Q7370306","display_name":"Rotation formalisms in three dimensions","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4832000136375427},{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.46140000224113464},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45750001072883606},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4404999911785126},{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.39890000224113464},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.36579999327659607},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32589998841285706},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2847000062465668},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2531000077724457},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i6.42424","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42424","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/42424","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/42424","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i6.42424","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i6.42424","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.6703441739082336}],"awards":[{"id":"https://openalex.org/G6826883195","display_name":null,"funder_award_id":"62201485","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G818396220","display_name":null,"funder_award_id":"62322318","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Deep":[0],"learning":[1],"has":[2],"achieved":[3],"remarkable":[4],"success":[5],"in":[6,17],"image":[7,121,139],"recognition,":[8],"yet":[9],"their":[10],"inherent":[11],"opacity":[12],"poses":[13],"challenges":[14],"for":[15],"deployment":[16],"critical":[18],"domains.":[19],"Concept-based":[20],"interpretations":[21],"aim":[22],"to":[23,95,129],"address":[24],"this":[25],"by":[26],"explaining":[27],"model":[28],"reasoning":[29],"through":[30],"human-understandable":[31],"concepts.":[32],"However,":[33],"existing":[34],"post-hoc":[35],"methods":[36],"and":[37,56,97,104,107,154],"ante-hoc":[38],"concept":[39,49,54,127],"bottleneck":[40],"models":[41,93],"(CBMs),":[42],"suffer":[43],"from":[44,85],"limitations":[45],"such":[46],"as":[47],"unreliable":[48],"relevance,":[50,106],"non-visual":[51],"or":[52],"labor-intensive":[53],"definitions,":[55],"model/data-agnostic":[57],"assumptions.":[58],"This":[59],"paper":[60],"introduces":[61],"Post-hoc":[62],"Concept":[63],"Bottleneck":[64],"Model":[65],"via":[66,112],"Representation":[67],"Decomposition":[68],"(PCBM-ReD),":[69],"a":[70,86],"novel":[71],"pipeline":[72],"that":[73],"retrofits":[74],"interpretability":[75],"onto":[76],"pretrained":[77],"opaque":[78],"models.":[79],"PCBM-ReD":[80,143],"automatically":[81],"extracts":[82],"visual":[83,102],"concepts":[84,99],"pre-trained":[87],"encoder,":[88],"employs":[89],"multimodal":[90],"large":[91],"language":[92],"(MLLMs)":[94],"label":[96],"filter":[98],"based":[100],"on":[101],"identifiability":[103],"task":[105],"selects":[108],"an":[109],"independent":[110],"subset":[111],"reconstruction-guided":[113],"optimization.":[114],"Leveraging":[115],"CLIP\u2019s":[116],"visual-text":[117],"alignment,":[118],"it":[119],"decomposes":[120],"representations":[122],"into":[123,131],"linear":[124],"combination":[125],"of":[126],"embeddings":[128],"fit":[130],"the":[132,148],"CBMs":[133],"abstraction.":[134],"Extensive":[135],"experiments":[136],"across":[137],"11":[138],"classification":[140],"tasks":[141],"show":[142],"achieves":[144],"state-of-the-art":[145],"accuracy,":[146],"narrows":[147],"performance":[149],"gap":[150],"with":[151],"end-to-end":[152],"models,":[153],"exhibits":[155],"better":[156],"interpretability.":[157]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}