{"id":"https://openalex.org/W4402353427","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650186","title":"QMKD: A Two-Stage Approach to Enhance Multi-Teacher Knowledge Distillation","display_name":"QMKD: A Two-Stage Approach to Enhance Multi-Teacher Knowledge Distillation","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402353427","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650186"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650186","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650186","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":"article","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/A5108847183","display_name":"Y.-C. Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"YuXing Lee","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101960931","display_name":"Wei Wu","orcid":"https://orcid.org/0000-0002-2694-6086"},"institutions":[{"id":"https://openalex.org/I2722730","display_name":"Inner Mongolia University","ror":"https://ror.org/0106qb496","country_code":"CN","type":"education","lineage":["https://openalex.org/I2722730"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wu","raw_affiliation_strings":["Inner Mongolia University,Department of Computer Science,Hohhot,China"],"affiliations":[{"raw_affiliation_string":"Inner Mongolia University,Department of Computer Science,Hohhot,China","institution_ids":["https://openalex.org/I2722730"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108847183"],"corresponding_institution_ids":["https://openalex.org/I2722730"],"apc_list":null,"apc_paid":null,"fwci":1.0911,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.81314999,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.960099995136261,"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/T11902","display_name":"Intelligent Tutoring Systems and Adaptive Learning","score":0.960099995136261,"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/T11122","display_name":"Online Learning and Analytics","score":0.940500020980835,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10731","display_name":"Educational Games and Gamification","score":0.9265999794006348,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.831334114074707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5795207619667053},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.5617461800575256},{"id":"https://openalex.org/keywords/process-engineering","display_name":"Process engineering","score":0.39340096712112427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33808717131614685},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.20248231291770935},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.19295528531074524},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17841356992721558},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08319598436355591}],"concepts":[{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.831334114074707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5795207619667053},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.5617461800575256},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.39340096712112427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33808717131614685},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.20248231291770935},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.19295528531074524},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17841356992721558},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08319598436355591},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650186","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650186","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1532688806","https://openalex.org/W1686810756","https://openalex.org/W1690739335","https://openalex.org/W1797268635","https://openalex.org/W1821462560","https://openalex.org/W1958236864","https://openalex.org/W2194775991","https://openalex.org/W2561238782","https://openalex.org/W2743289088","https://openalex.org/W2747909401","https://openalex.org/W2750432752","https://openalex.org/W2883780447","https://openalex.org/W2948582784","https://openalex.org/W2963125010","https://openalex.org/W2963140444","https://openalex.org/W2963163009","https://openalex.org/W2964137095","https://openalex.org/W2995607862","https://openalex.org/W3099225546","https://openalex.org/W3118608800","https://openalex.org/W3174510164","https://openalex.org/W3176403475","https://openalex.org/W3177196641","https://openalex.org/W3189117283","https://openalex.org/W3212445569","https://openalex.org/W4224927203","https://openalex.org/W4304091718","https://openalex.org/W4312358159","https://openalex.org/W4386075960","https://openalex.org/W4386597250","https://openalex.org/W6631864160","https://openalex.org/W6784838754","https://openalex.org/W6804171142"],"related_works":["https://openalex.org/W3085764877","https://openalex.org/W2514414740","https://openalex.org/W2377414158","https://openalex.org/W3199615306","https://openalex.org/W77207468","https://openalex.org/W3212781313","https://openalex.org/W4307725381","https://openalex.org/W124863575","https://openalex.org/W3203147184","https://openalex.org/W2037691954"],"abstract_inverted_index":{"Knowledge":[0],"distillation":[1,26,69,114,122,186],"serves":[2],"as":[3],"an":[4],"effective":[5],"model":[6,15,37,41],"compression":[7],"technique,":[8],"enhancing":[9,111],"the":[10,17,39,44,52,57,112,120,143,152,159,165],"performance":[11,170],"of":[12,19],"a":[13,83,89],"smaller":[14],"through":[16],"transfer":[18,138],"knowledge.":[20],"Previous":[21],"research":[22],"on":[23,30,171],"multi-teacher":[24,67,184],"knowledge":[25,68,113,121,137,185],"has":[27],"predominantly":[28],"focused":[29],"exploring":[31],"feature":[32],"correlations":[33],"between":[34,79,155],"each":[35],"teacher":[36,104],"and":[38,82,107,127,158],"student":[40,108],"to":[42,75,98,135,142,149,181],"improve":[43],"student's":[45],"performance.":[46],"However,":[47],"these":[48],"methods":[49],"often":[50],"overlook":[51],"potential":[53],"information":[54,74,101],"embedded":[55],"in":[56],"soft":[58,105],"labels":[59,106],"generated":[60],"by":[61,71],"teachers.":[62],"This":[63,86],"paper":[64,87],"delves":[65],"into":[66,123],"techniques":[70],"leveraging":[72],"soft-label":[73],"uncover":[76],"latent":[77,100,153],"associations":[78,154],"multiple":[80,140,156],"teachers":[81,141,157],"single":[84],"student.":[85,144,160],"introduces":[88],"novel":[90],"method":[91,167],"called":[92],"QMKD,":[93],"which":[94],"utilizes":[95],"reinforcement":[96],"learning":[97],"extract":[99],"from":[102,139],"both":[103],"representations,":[109],"thereby":[110],"process.":[115],"The":[116],"proposed":[117,166],"approach":[118],"divides":[119],"two":[124],"stages:":[125],"NAKD":[126,131],"RAKD.":[128],"During":[129],"training,":[130],"is":[132,147],"initially":[133],"employed":[134],"facilitate":[136],"Subsequently,":[145],"RAKD":[146],"applied":[148],"further":[150],"explore":[151],"Experimental":[161],"results":[162],"demonstrate":[163],"that":[164],"exhibits":[168],"superior":[169],"classical":[172],"datasets.":[173],"Additionally,":[174],"it":[175],"consumes":[176],"fewer":[177],"computational":[178],"resources":[179],"compared":[180],"traditional":[182],"feature-based":[183],"methods.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
