{"id":"https://openalex.org/W4401350014","doi":"https://doi.org/10.48550/arxiv.2408.07080","title":"DisCoM-KD: Cross-Modal Knowledge Distillation via Disentanglement\n Representation and Adversarial Learning","display_name":"DisCoM-KD: Cross-Modal Knowledge Distillation via Disentanglement\n Representation and Adversarial Learning","publication_year":2024,"publication_date":"2024-08-05","ids":{"openalex":"https://openalex.org/W4401350014","doi":"https://doi.org/10.48550/arxiv.2408.07080"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.07080","pdf_url":"http://arxiv.org/pdf/2408.07080","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"http://arxiv.org/pdf/2408.07080","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018231294","display_name":"Dino Ienco","orcid":"https://orcid.org/0000-0002-8736-3132"},"institutions":[{"id":"https://openalex.org/I4210122476","display_name":"Territoires","ror":"https://ror.org/026tc4g97","country_code":"FR","type":"facility","lineage":["https://openalex.org/I198244214","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I4210088668","https://openalex.org/I4210104684","https://openalex.org/I4210122476"]},{"id":"https://openalex.org/I4387153996","display_name":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","ror":"https://ror.org/0458hw939","country_code":null,"type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I131077856","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I4210088668","https://openalex.org/I4387153996"]},{"id":"https://openalex.org/I4210088668","display_name":"Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement","ror":"https://ror.org/003vg9w96","country_code":"FR","type":"government","lineage":["https://openalex.org/I4210088668"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Dino Ienco","raw_affiliation_strings":["EVERGREEN - Observation de la terre et apprentissage machine pour les d\u00e9fis agro-environnementaux (2004 route des Lucioles 06902 Sophia Antipolis - France)","INRAE - Institut National de Recherche pour l\u2019Agriculture, l\u2019Alimentation et l\u2019Environnement (France)","UMR TETIS - Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale (Maison de la t\u00e9l\u00e9d\u00e9tection - 500 rue Jean-Fran\u00e7ois Breton - 34093 Montpellier Cedex 5 - France)"],"affiliations":[{"raw_affiliation_string":"EVERGREEN - Observation de la terre et apprentissage machine pour les d\u00e9fis agro-environnementaux (2004 route des Lucioles 06902 Sophia Antipolis - France)","institution_ids":[]},{"raw_affiliation_string":"UMR TETIS - Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale (Maison de la t\u00e9l\u00e9d\u00e9tection - 500 rue Jean-Fran\u00e7ois Breton - 34093 Montpellier Cedex 5 - France)","institution_ids":["https://openalex.org/I4210122476","https://openalex.org/I4387153996"]},{"raw_affiliation_string":"INRAE - Institut National de Recherche pour l\u2019Agriculture, l\u2019Alimentation et l\u2019Environnement (France)","institution_ids":["https://openalex.org/I4210088668"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022088234","display_name":"C\u00e1ssio F. Dantas","orcid":"https://orcid.org/0000-0002-1934-0625"},"institutions":[{"id":"https://openalex.org/I4210122476","display_name":"Territoires","ror":"https://ror.org/026tc4g97","country_code":"FR","type":"facility","lineage":["https://openalex.org/I198244214","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I4210088668","https://openalex.org/I4210104684","https://openalex.org/I4210122476"]},{"id":"https://openalex.org/I4387153996","display_name":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","ror":"https://ror.org/0458hw939","country_code":null,"type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I131077856","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I4210088668","https://openalex.org/I4387153996"]},{"id":"https://openalex.org/I4210088668","display_name":"Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement","ror":"https://ror.org/003vg9w96","country_code":"FR","type":"government","lineage":["https://openalex.org/I4210088668"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Cassio Fraga Dantas","raw_affiliation_strings":["EVERGREEN - Observation de la terre et apprentissage machine pour les d\u00e9fis agro-environnementaux (2004 route des Lucioles 06902 Sophia Antipolis - France)","INRAE - Institut National de Recherche pour l\u2019Agriculture, l\u2019Alimentation et l\u2019Environnement (France)","UMR TETIS - Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale (Maison de la t\u00e9l\u00e9d\u00e9tection - 500 rue Jean-Fran\u00e7ois Breton - 34093 Montpellier Cedex 5 - France)"],"affiliations":[{"raw_affiliation_string":"UMR TETIS - Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale (Maison de la t\u00e9l\u00e9d\u00e9tection - 500 rue Jean-Fran\u00e7ois Breton - 34093 Montpellier Cedex 5 - France)","institution_ids":["https://openalex.org/I4210122476","https://openalex.org/I4387153996"]},{"raw_affiliation_string":"INRAE - Institut National de Recherche pour l\u2019Agriculture, l\u2019Alimentation et l\u2019Environnement (France)","institution_ids":["https://openalex.org/I4210088668"]},{"raw_affiliation_string":"EVERGREEN - Observation de la terre et apprentissage machine pour les d\u00e9fis agro-environnementaux (2004 route des Lucioles 06902 Sophia Antipolis - France)","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.901841,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":77,"max":88},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9911,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9911,"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/representation","display_name":"Representation","score":0.70699257}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.833863},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.76187515},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.70699257},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.54847866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46174318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34841627},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.16638765},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.119896024},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0657168},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"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":[{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.07080","pdf_url":"http://arxiv.org/pdf/2408.07080","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://hal.science/hal-04666307","pdf_url":"https://hal.science/hal-04666307/document","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.07080","pdf_url":"http://arxiv.org/pdf/2408.07080","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.76,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4310988119","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W4285226279","https://openalex.org/W4246396837","https://openalex.org/W3191453585","https://openalex.org/W3126451824","https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W1561927205"],"abstract_inverted_index":{"Cross-modal":[0],"knowledge":[1,63,91,107,129,207],"distillation":[2,208],"(CMKD)":[3],"refers":[4],"to":[5,60,68,127,133,150,161,181,233,244],"the":[6,33,58,73,87,96,125,167,179,190,214,235],"scenario":[7],"in":[8,86],"which":[9],"a":[10,21,46,50,65,69,93,102,134,162],"learning":[11,145],"framework":[12,104,172],"must":[13],"handle":[14],"training":[15,26],"and":[16,27,157,201,226],"test":[17,28],"data":[18,29,37,56,132,243],"that":[19,116],"exhibit":[20],"modality":[22],"mismatch,":[23],"more":[24],"precisely,":[25],"do":[30],"not":[31],"cover":[32],"same":[34],"set":[35],"of":[36,76,89,121,216],"modalities.":[38,228],"Traditional":[39],"approaches":[40],"for":[41,105,238],"CMKD":[42],"are":[43],"based":[44,112],"on":[45,54,196],"teacher/student":[47,97,169],"paradigm":[48,237],"where":[49],"teacher":[51,67,191],"is":[52],"trained":[53],"multi-modal":[55,66,131,199,242],"with":[57,124,146],"aim":[59,126],"successively":[61],"distill":[62],"from":[64,130,241],"single-modal":[70,135,176,245],"student.":[71],"Despite":[72],"widespread":[74],"adoption":[75],"such":[77],"paradigm,":[78,98,170],"recent":[79,205],"research":[80],"has":[81],"highlighted":[82],"its":[83,203],"inherent":[84],"limitations":[85],"context":[88],"cross-modal":[90,106],"transfer.Taking":[92],"step":[94],"beyond":[95],"here":[99],"we":[100],"introduce":[101],"new":[103],"distillation,":[108],"named":[109],"DisCoM-KD":[110,140,195,217],"(Disentanglement-learning":[111],"Cross-Modal":[113],"Knowledge":[114],"Distillation),":[115],"explicitly":[117],"models":[118],"different":[119],"types":[120],"per-modality":[122],"information":[123,240],"transfer":[128],"classifier.":[136,192],"To":[137],"this":[138],"end,":[139],"effectively":[141],"combines":[142],"disentanglement":[143],"representation":[144],"adversarial":[147],"domain":[148],"adaptation":[149],"simultaneously":[151,173],"extract,":[152],"foreach":[153],"modality,":[154],"domain-invariant,":[155],"domain-informative":[156],"domain-irrelevant":[158],"features":[159],"according":[160],"specific":[163],"downstream":[164],"task.":[165],"Unlike":[166],"traditional":[168,236],"our":[171],"learns":[174],"all":[175],"classifiers,":[177],"eliminating":[178],"need":[180],"learn":[182],"each":[183],"student":[184],"model":[185],"separately":[186],"as":[187,189],"well":[188],"We":[193],"evaluated":[194],"three":[197],"standard":[198],"benchmarks":[200],"compared":[202],"behaviourwith":[204],"SOTA":[206],"frameworks.":[209],"The":[210],"findings":[211],"clearly":[212],"demonstrate":[213],"effectiveness":[215],"over":[218],"competitors":[219],"considering":[220],"mismatch":[221],"scenarios":[222],"involving":[223],"both":[224],"overlapping":[225],"non-overlapping":[227],"These":[229],"results":[230],"offer":[231],"insights":[232],"reconsider":[234],"distilling":[239],"neural":[246],"networks.":[247]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4401350014","counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-04-18T09:28:47.069797","created_date":"2024-08-06"}