{"id":"https://openalex.org/W4388963903","doi":"https://doi.org/10.48550/arxiv.2311.13594","title":"Labeling Neural Representations with Inverse Recognition","display_name":"Labeling Neural Representations with Inverse Recognition","publication_year":2023,"publication_date":"2023-11-22","ids":{"openalex":"https://openalex.org/W4388963903","doi":"https://doi.org/10.48550/arxiv.2311.13594"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2311.13594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.13594","pdf_url":"https://arxiv.org/pdf/2311.13594","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2311.13594","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070294236","display_name":"Kirill Bykov","orcid":"https://orcid.org/0000-0002-3358-2858"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bykov, Kirill","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093100519","display_name":"Laura Kopf","orcid":"https://orcid.org/0009-0005-4280-3818"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kopf, Laura","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034738514","display_name":"Shinichi Nakajima","orcid":"https://orcid.org/0000-0003-3970-4569"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nakajima, Shinichi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091841504","display_name":"Marius Kloft","orcid":"https://orcid.org/0000-0001-6829-3725"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kloft, Marius","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5026720807","display_name":"Marina M. -C. H\u00f6hne","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"H\u00f6hne, Marina M. -C.","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5070294236"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"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":0.9979000091552734,"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":0.9979000091552734,"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":0.9912999868392944,"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/T10320","display_name":"Neural Networks and Applications","score":0.9753999710083008,"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/spurious-relationship","display_name":"Spurious relationship","score":0.7503184080123901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.725407063961029},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6635156869888306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6256505250930786},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5998281240463257},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5712661147117615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5645397305488586},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.540192723274231},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4504290223121643},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.43725529313087463},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.41821372509002686},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4111180305480957},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3708708882331848}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.7503184080123901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.725407063961029},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6635156869888306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6256505250930786},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5998281240463257},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5712661147117615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5645397305488586},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.540192723274231},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4504290223121643},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.43725529313087463},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.41821372509002686},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4111180305480957},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3708708882331848},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2311.13594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.13594","pdf_url":"https://arxiv.org/pdf/2311.13594","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2311.13594","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2311.13594","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":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2311.13594","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.13594","pdf_url":"https://arxiv.org/pdf/2311.13594","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388963903.pdf","grobid_xml":"https://content.openalex.org/works/W4388963903.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3113091479","https://openalex.org/W2162899405","https://openalex.org/W941090075","https://openalex.org/W2044987316","https://openalex.org/W3134374554","https://openalex.org/W2237480245","https://openalex.org/W2113265763","https://openalex.org/W2952313066","https://openalex.org/W4300000045","https://openalex.org/W2526749411"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"(DNNs)":[3],"demonstrate":[4,123],"remarkable":[5],"capabilities":[6],"in":[7,128],"learning":[8],"complex":[9],"hierarchical":[10,145],"data":[11],"representations,":[12],"but":[13],"the":[14,94,106,109,124,132,141,144,150],"nature":[15],"of":[16,39,79,83,96,119,126,134,143,147],"these":[17,69],"representations":[18,58,135],"remains":[19],"largely":[20],"unknown.":[21],"Existing":[22],"global":[23],"explainability":[24],"methods,":[25],"such":[26,32],"as":[27,33],"Network":[28],"Dissection,":[29],"face":[30],"limitations":[31],"reliance":[34],"on":[35,93],"segmentation":[36,97],"masks,":[37],"lack":[38],"statistical":[40,120],"significance":[41],"testing,":[42],"and":[43,89,111,115,140],"high":[44],"computational":[45,87],"demands.":[46],"We":[47,122],"propose":[48],"Inverse":[49],"Recognition":[50],"(INVERT),":[51],"a":[52,117],"scalable":[53],"approach":[54],"for":[55],"connecting":[56],"learned":[57],"with":[59],"human-understandable":[60],"concepts":[61],"by":[62,137],"leveraging":[63],"their":[64],"capacity":[65],"to":[66,73],"discriminate":[67],"between":[68,108],"concepts.":[70],"In":[71],"contrast":[72],"prior":[74],"work,":[75],"INVERT":[76,100,127],"is":[77],"capable":[78],"handling":[80],"diverse":[81],"types":[82],"neurons,":[84],"exhibits":[85],"less":[86],"complexity,":[88],"does":[90],"not":[91],"rely":[92],"availability":[95],"masks.":[98],"Moreover,":[99],"provides":[101],"an":[102],"interpretable":[103],"metric":[104],"assessing":[105],"alignment":[107],"representation":[110],"its":[112],"corresponding":[113],"explanation":[114],"delivering":[116],"measure":[118],"significance.":[121],"applicability":[125],"various":[129],"scenarios,":[130],"including":[131],"identification":[133],"affected":[136],"spurious":[138],"correlations,":[139],"interpretation":[142],"structure":[146],"decision-making":[148],"within":[149],"models.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
