{"id":"https://openalex.org/W3214140015","doi":"https://doi.org/10.1109/bigdata52589.2021.9671988","title":"Learning Interpretation with Explainable Knowledge Distillation","display_name":"Learning Interpretation with Explainable Knowledge Distillation","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W3214140015","doi":"https://doi.org/10.1109/bigdata52589.2021.9671988","mag":"3214140015"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata52589.2021.9671988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671988","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2111.06945","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075926625","display_name":"Raed Alharbi","orcid":"https://orcid.org/0000-0003-0247-3824"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Raed Alharbi","raw_affiliation_strings":["Computer and Information Science and Engineering Department, University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"Computer and Information Science and Engineering Department, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063231826","display_name":"Minh N. Vu","orcid":"https://orcid.org/0000-0001-8727-0350"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Minh N. Vu","raw_affiliation_strings":["Computer and Information Science and Engineering Department, University of Florida, Gainesville, FL, USA"],"affiliations":[{"raw_affiliation_string":"Computer and Information Science and Engineering Department, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005663679","display_name":"My T. Thai","orcid":"https://orcid.org/0000-0003-0503-2012"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"My T. Thai","raw_affiliation_strings":["Computer and Information Science and Engineering Department, University of Florida, Gainesville, FL, USA","University of Florida"],"affiliations":[{"raw_affiliation_string":"Computer and Information Science and Engineering Department, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]},{"raw_affiliation_string":"University of Florida","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075926625"],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13861935,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"705","last_page":"714"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9979000091552734,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9902999997138977,"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/divergence","display_name":"Divergence (linguistics)","score":0.7961130142211914},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.7751129865646362},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.646093487739563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5804941654205322},{"id":"https://openalex.org/keywords/interpretation","display_name":"Interpretation (philosophy)","score":0.5716748237609863},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5272499322891235},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5172939300537109},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.46952763199806213},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.11112359166145325},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.0852138102054596}],"concepts":[{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.7961130142211914},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.7751129865646362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.646093487739563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5804941654205322},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.5716748237609863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5272499322891235},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5172939300537109},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.46952763199806213},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.11112359166145325},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0852138102054596},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/bigdata52589.2021.9671988","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata52589.2021.9671988","pdf_url":null,"source":{"id":"https://openalex.org/S4363607718","display_name":"2021 IEEE International Conference on Big Data (Big Data)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2111.06945","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.06945","pdf_url":"https://arxiv.org/pdf/2111.06945","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3214140015","is_oa":true,"landing_page_url":"http://arxiv.org/pdf/2111.06945.pdf","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2111.06945","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2111.06945","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2111.06945","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.06945","pdf_url":"https://arxiv.org/pdf/2111.06945","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8500000238418579}],"awards":[{"id":"https://openalex.org/G1490481123","display_name":null,"funder_award_id":"1939725","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3214140015.pdf","grobid_xml":"https://content.openalex.org/works/W3214140015.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1508404128","https://openalex.org/W1652388399","https://openalex.org/W1821462560","https://openalex.org/W2007339694","https://openalex.org/W2112796928","https://openalex.org/W2136655611","https://openalex.org/W2139427956","https://openalex.org/W2177066871","https://openalex.org/W2182396527","https://openalex.org/W2254039850","https://openalex.org/W2282821441","https://openalex.org/W2295107390","https://openalex.org/W2561238782","https://openalex.org/W2621614835","https://openalex.org/W2731516819","https://openalex.org/W2962766617","https://openalex.org/W2962835968","https://openalex.org/W2962858109","https://openalex.org/W2962862931","https://openalex.org/W2963674932","https://openalex.org/W2964111476","https://openalex.org/W2981731882","https://openalex.org/W2982207148","https://openalex.org/W2982242214","https://openalex.org/W2988157455","https://openalex.org/W3004127093","https://openalex.org/W3016970897","https://openalex.org/W3101026663","https://openalex.org/W3118608800","https://openalex.org/W3138819813","https://openalex.org/W3187772171","https://openalex.org/W6637373629","https://openalex.org/W6638523607","https://openalex.org/W6737947904","https://openalex.org/W6740493225","https://openalex.org/W6784653527","https://openalex.org/W6787972765","https://openalex.org/W6842607031"],"related_works":["https://openalex.org/W3026294878","https://openalex.org/W2903566196","https://openalex.org/W3177418761","https://openalex.org/W2920873626","https://openalex.org/W3207917192","https://openalex.org/W1597703949","https://openalex.org/W2578095432","https://openalex.org/W2622005879","https://openalex.org/W2259567770","https://openalex.org/W2396791900","https://openalex.org/W2292523511","https://openalex.org/W2005245367","https://openalex.org/W3113553002","https://openalex.org/W2407307256","https://openalex.org/W3038107861","https://openalex.org/W2963226382","https://openalex.org/W2042450654","https://openalex.org/W3099298437","https://openalex.org/W3088117111","https://openalex.org/W1486204617"],"abstract_inverted_index":{"Knowledge":[0],"Distillation":[1],"(KD)":[2],"has":[3],"been":[4],"considered":[5],"as":[6,44],"a":[7,20,28,82],"key":[8],"solution":[9],"in":[10,15,46,139],"model":[11,23,31,103,110],"compression":[12],"and":[13],"acceleration":[14],"recent":[16],"years.":[17],"In":[18,77],"KD,":[19],"small":[21],"student":[22,106],"is":[24],"generally":[25],"trained":[26,127,132],"from":[27,100],"large":[29],"teacher":[30,60,102,120,149],"by":[32,70,128,133],"minimizing":[33],"the":[34,37,41,59,62,65,71,93,95,101,105,112,119,148],"divergence":[35],"between":[36],"probabilistic":[38],"outputs":[39],"of":[40,58,67,114,141],"two.":[42],"However,":[43],"demonstrated":[45],"our":[47],"experiments,":[48],"existing":[49],"KD":[50,135],"methods":[51,136],"might":[52],"not":[53,75,137],"transfer":[54],"critical":[55],"explainable":[56,84],"knowledge":[57,85],"to":[61,104,117,147],"student,":[63],"i.e.":[64],"explanations":[66],"predictions":[68],"made":[69],"two":[72],"models":[73,126],"are":[74,98],"consistent.":[76],"this":[78],"paper,":[79],"we":[80],"propose":[81],"novel":[83],"distillation":[86],"model,":[87],"called":[88],"XDistillation,":[89],"through":[90],"which":[91],"both":[92],"performance":[94],"explanations\u2019":[96],"information":[97],"transferred":[99],"model.":[107],"The":[108],"XDistillation":[109,129],"leverages":[111],"idea":[113],"convolutional":[115],"autoencoders":[116],"approximate":[118],"explanations.":[121],"Our":[122],"experiments":[123],"shows":[124],"that":[125],"outperform":[130],"those":[131],"conventional":[134],"only":[138],"term":[140],"predictive":[142],"accuracy":[143],"but":[144],"also":[145],"faithfulness":[146],"models.":[150]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}