{"id":"https://openalex.org/W4402353865","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650232","title":"Concept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNet","display_name":"Concept Visualization: Explaining the CLIP Multi-modal Embedding Using WordNet","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402353865","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650232"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650232","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081601581","display_name":"Loris Giulivi","orcid":"https://orcid.org/0000-0001-7027-4726"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Loris Giulivi","raw_affiliation_strings":["Politecnico di Milano,DEIB"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,DEIB","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006716646","display_name":"Giacomo Boracchi","orcid":"https://orcid.org/0000-0002-1650-3054"},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giacomo Boracchi","raw_affiliation_strings":["Politecnico di Milano,DEIB"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Milano,DEIB","institution_ids":["https://openalex.org/I93860229"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I93860229"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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/T10028","display_name":"Topic Modeling","score":0.9988999962806702,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9976999759674072,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9937999844551086,"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/wordnet","display_name":"WordNet","score":0.9130140542984009},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7814540863037109},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7263355255126953},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.7172401547431946},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6771586537361145},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.43384864926338196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4281467795372009},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41987839341163635},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.40792179107666016}],"concepts":[{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.9130140542984009},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7814540863037109},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7263355255126953},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.7172401547431946},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6771586537361145},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43384864926338196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4281467795372009},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41987839341163635},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.40792179107666016},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650232","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10650232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:re.public.polimi.it:11311/1288717","is_oa":false,"landing_page_url":"https://hdl.handle.net/11311/1288717","pdf_url":null,"source":{"id":"https://openalex.org/S4306400312","display_name":"Virtual Community of Pathological Anatomy (University of Castilla La Mancha)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79189158","host_organization_name":"University of Castilla-La Mancha","host_organization_lineage":["https://openalex.org/I79189158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1797268635","https://openalex.org/W1861492603","https://openalex.org/W2081580037","https://openalex.org/W2117539524","https://openalex.org/W2295107390","https://openalex.org/W2296719434","https://openalex.org/W2594475271","https://openalex.org/W2787091153","https://openalex.org/W2883554151","https://openalex.org/W2901114541","https://openalex.org/W2962858109","https://openalex.org/W2963045696","https://openalex.org/W2964274719","https://openalex.org/W2981731882","https://openalex.org/W2992308087","https://openalex.org/W3004725381","https://openalex.org/W3010300896","https://openalex.org/W3035371891","https://openalex.org/W3035712793","https://openalex.org/W3113107791","https://openalex.org/W4224035735","https://openalex.org/W4224928659","https://openalex.org/W4286905471","https://openalex.org/W4300235091","https://openalex.org/W4312933868","https://openalex.org/W4390874575","https://openalex.org/W4399419713","https://openalex.org/W4399929809","https://openalex.org/W6620707391","https://openalex.org/W6638319203","https://openalex.org/W6734862562","https://openalex.org/W6752170072","https://openalex.org/W6763878013","https://openalex.org/W6791353385","https://openalex.org/W6802159084","https://openalex.org/W6809885388","https://openalex.org/W6810151021","https://openalex.org/W6810541688","https://openalex.org/W6811013733"],"related_works":["https://openalex.org/W2900382651","https://openalex.org/W1981879262","https://openalex.org/W2363417484","https://openalex.org/W4225863708","https://openalex.org/W1599970036","https://openalex.org/W1480103567","https://openalex.org/W158852162","https://openalex.org/W1849827364","https://openalex.org/W2786299737","https://openalex.org/W115324854"],"abstract_inverted_index":{"Advances":[0],"in":[1,5,13,43,54,93],"multi-modal":[2,148],"embeddings,":[3],"and":[4,47,192,206],"particular":[6],"CLIP,":[7],"have":[8],"recently":[9],"driven":[10],"several":[11],"breakthroughs":[12],"Computer":[14],"Vision":[15],"(CV).":[16],"CLIP":[17,39,106,140],"has":[18],"shown":[19],"impressive":[20],"performance":[21],"on":[22,65,195,226],"a":[23,111,133,215],"variety":[24],"of":[25,36,103,114,142,150,156,183,188],"tasks,":[26],"yet,":[27],"its":[28],"inherently":[29],"opaque":[30],"architecture":[31],"may":[32],"hinder":[33],"the":[34,55,88,96,101,115,119,139,147,151,173,208,227],"application":[35],"models":[37,63,104],"employing":[38],"as":[40,53,107],"backbone,":[41,110],"especially":[42],"fields":[44],"where":[45],"trust":[46],"model":[48,175],"explainability":[49],"are":[50],"imperative,":[51],"such":[52],"medical":[56],"domain.":[57],"Current":[58],"explanation":[59],"methodologies":[60],"for":[61,166],"CV":[62],"rely":[64],"Saliency":[66,77,164],"Maps":[67,78,165],"computed":[68,82],"through":[69],"gradient":[70],"analysis":[71],"or":[72],"input":[73],"perturbation.":[74],"However,":[75],"these":[76],"can":[79,222],"only":[80],"be":[81],"to":[83,87,161,171],"explain":[84],"classes":[85],"relevant":[86],"end":[89,174],"task,":[90],"often":[91],"smaller":[92],"scope":[94],"than":[95],"backbone":[97],"training":[98],"classes.":[99],"In":[100],"context":[102],"implementing":[105],"their":[108],"vision":[109],"substantial":[112],"portion":[113],"information":[116,158],"embedded":[117],"within":[118],"learned":[120],"representations":[121],"is":[122],"thus":[123],"left":[124],"unexplained.In":[125],"this":[126],"work,":[127],"we":[128,213],"propose":[129],"Concept":[130,202],"Visualization":[131],"(ConVis),":[132],"novel":[134],"saliency":[135],"methodology":[136,221],"that":[137,201,219],"explains":[138],"embedding":[141],"an":[143,186,196],"image":[144],"by":[145],"exploiting":[146],"nature":[149],"embeddings.":[152],"ConVis":[153,194],"makes":[154],"use":[155,182],"lexical":[157],"from":[159],"WordNet":[160,184],"compute":[162],"task-agnostic":[163],"any":[167],"concept,":[168],"not":[169],"limited":[170],"concepts":[172],"was":[176],"trained":[177],"on.":[178],"We":[179],"validate":[180],"our":[181,220],"via":[185],"out":[187],"distribution":[189],"detection":[190],"experiment,":[191],"test":[193],"object":[197],"localization":[198],"benchmark,":[199],"showing":[200],"Visualizations":[203],"correctly":[204],"identify":[205],"localize":[207],"image\u2019s":[209],"semantic":[210],"content.":[211],"Additionally,":[212],"perform":[214],"user":[216],"study":[217],"demonstrating":[218],"give":[223],"users":[224],"insight":[225],"model\u2019s":[228],"functioning.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}