{"id":"https://openalex.org/W7135219750","doi":"https://doi.org/10.48550/arxiv.2603.11795","title":"Intrinsic Concept Extraction Based on Compositional Interpretability","display_name":"Intrinsic Concept Extraction Based on Compositional Interpretability","publication_year":2026,"publication_date":"2026-03-12","ids":{"openalex":"https://openalex.org/W7135219750","doi":"https://doi.org/10.48550/arxiv.2603.11795"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.11795","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11795","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.11795","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128988334","display_name":"Hanyu Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Hanyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128976150","display_name":"Hong Tao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao, Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129090295","display_name":"Guoheng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Guoheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128979271","display_name":"Jianbin Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Jianbin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128933909","display_name":"Xuhang Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Xuhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129000793","display_name":"Chi-Man Pun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pun, Chi-Man","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129012618","display_name":"Shanhu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shanhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129033634","display_name":"Pan Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Pan","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":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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.23100000619888306,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.23100000619888306,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.13009999692440033,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0689999982714653,"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/interpretability","display_name":"Interpretability","score":0.8133999705314636},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6618000268936157},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6061000227928162},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5666999816894531},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4016999900341034},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.3869999945163727}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8133999705314636},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7339000105857849},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6618000268936157},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6061000227928162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5957000255584717},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5666999816894531},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4016999900341034},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39590001106262207},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3571999967098236},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3411000072956085},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3052999973297119},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C76363472","wikidata":"https://www.wikidata.org/wiki/Q1437394","display_name":"Formal concept analysis","level":2,"score":0.26080000400543213}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.11795","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11795","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.11795","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.11795","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5872547626495361}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unsupervised":[0],"Concept":[1,37],"Extraction":[2,38],"aims":[3,43],"to":[4,18,44,49,111,139],"extract":[5,19,50],"concepts":[6,55,158],"from":[7,15,56,159],"a":[8,29,57,80,97,129,160],"single":[9,58,161],"image;":[10],"however,":[11],"existing":[12],"methods":[13],"suffer":[14],"the":[16,62,69,86,103,118,135],"inability":[17],"composable":[20,51],"intrinsic":[21,157],"concepts.":[22,73],"To":[23,74],"address":[24],"this,":[25],"this":[26,76],"paper":[27],"introduces":[28],"new":[30],"task":[31,42,88],"called":[32,82],"Compositional":[33],"and":[34,53,121],"Interpretable":[35],"Intrinsic":[36],"(CI-ICE).":[39],"The":[40],"CI-ICE":[41,87],"leverage":[45],"diffusion-based":[46],"text-to-image":[47],"models":[48],"object-level":[52],"attribute-level":[54],"image,":[59],"such":[60],"that":[61,101,133],"original":[63],"concept":[64,98,114,136,146],"can":[65],"be":[66],"reconstructed":[67],"through":[68,89],"combination":[70],"of":[71,108],"these":[72],"achieve":[75,112],"goal,":[77],"we":[78,95,127],"propose":[79,96],"method":[81,132,149],"HyperExpress,":[83],"which":[84],"addresses":[85],"two":[90],"core":[91],"aspects.":[92],"Specifically,":[93],"first,":[94],"learning":[99],"approach":[100],"leverages":[102],"inherent":[104],"hierarchical":[105,119],"modeling":[106],"capability":[107],"hyperbolic":[109],"space":[110,138],"accurate":[113],"disentanglement":[115],"while":[116,144],"preserving":[117],"structure":[120],"relational":[122],"dependencies":[123],"among":[124],"concepts;":[125],"second,":[126],"introduce":[128],"concept-wise":[130],"optimization":[131],"maps":[134],"embedding":[137],"maintain":[140],"complex":[141],"inter-concept":[142],"relationships":[143],"ensuring":[145],"composability.":[147],"Our":[148],"demonstrates":[150],"outstanding":[151],"performance":[152],"in":[153],"extracting":[154],"compositionally":[155],"interpretable":[156],"image.":[162]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-14T00:00:00"}
