{"id":"https://openalex.org/W7135100996","doi":"https://doi.org/10.48550/arxiv.2603.10084","title":"Digging Deeper: Learning Multi-Level Concept Hierarchies","display_name":"Digging Deeper: Learning Multi-Level Concept Hierarchies","publication_year":2026,"publication_date":"2026-03-10","ids":{"openalex":"https://openalex.org/W7135100996","doi":"https://doi.org/10.48550/arxiv.2603.10084"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10084","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10084","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.10084","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127813411","display_name":"Oscar Hill","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hill, Oscar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022801769","display_name":"Mateo Espinosa Zarlenga","orcid":"https://orcid.org/0009-0006-7333-5727"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zarlenga, Mateo Espinosa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5036018012","display_name":"Mateja Jamnik","orcid":"https://orcid.org/0000-0003-2772-2532"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jamnik, Mateja","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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9415000081062317,"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":0.9415000081062317,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.010200000368058681,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.003800000064074993,"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":0.8697999715805054},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6244999766349792},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6159999966621399},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.4156999886035919},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.3264000117778778},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3059999942779541}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8697999715805054},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6244999766349792},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6159999966621399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6036999821662903},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45080000162124634},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38769999146461487},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3061000108718872},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C76363472","wikidata":"https://www.wikidata.org/wiki/Q1437394","display_name":"Formal concept analysis","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C27415008","wikidata":"https://www.wikidata.org/wiki/Q7256382","display_name":"Psychological intervention","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C2779080342","wikidata":"https://www.wikidata.org/wiki/Q4232202","display_name":"Digging","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C48164120","wikidata":"https://www.wikidata.org/wiki/Q4491893","display_name":"Concept learning","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.2623000144958496}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10084","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10084","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.10084","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10084","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Although":[0],"concept-based":[1],"models":[2],"promise":[3],"interpretability":[4],"by":[5],"explaining":[6],"predictions":[7],"with":[8,66],"human-understandable":[9],"concepts,":[10],"they":[11],"typically":[12],"rely":[13],"on":[14],"exhaustive":[15],"annotations":[16],"and":[17,22,41,54,80,89,110],"treat":[18],"concepts":[19,106],"as":[20],"flat":[21],"independent.":[23],"To":[24],"circumvent":[25],"this,":[26],"recent":[27],"work":[28],"has":[29],"introduced":[30],"Hierarchical":[31],"Concept":[32,42,55,68],"Embedding":[33],"Models":[34],"(HiCEMs)":[35],"to":[36,44,59],"explicitly":[37],"model":[38],"concept":[39,74,119],"relationships,":[40],"Splitting":[43,56,69],"discover":[45],"sub-concepts":[46],"using":[47],"only":[48,77],"coarse":[49],"annotations.":[50],"However,":[51],"both":[52],"HiCEMs":[53],"are":[57],"restricted":[58],"shallow":[60],"hierarchies.":[61],"We":[62],"overcome":[63],"this":[64],"limitation":[65],"Multi-Level":[67],"(MLCS),":[70],"which":[71],"discovers":[72,104],"multi-level":[73],"hierarchies":[75,88],"from":[76],"top-level":[78],"supervision,":[79],"Deep-HiCEMs,":[81],"an":[82],"architecture":[83],"that":[84,102,111,121],"represents":[85],"these":[86],"discovered":[87],"enables":[90],"interventions":[91,120],"at":[92],"multiple":[93,99],"levels":[94],"of":[95],"abstraction.":[96],"Experiments":[97],"across":[98],"datasets":[100],"show":[101],"MLCS":[103],"human-interpretable":[105],"absent":[107],"during":[108],"training":[109],"Deep-HiCEMs":[112],"maintain":[113],"high":[114],"accuracy":[115],"while":[116],"supporting":[117],"test-time":[118],"can":[122],"improve":[123],"task":[124],"performance.":[125]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-13T00:00:00"}