{"id":"https://openalex.org/W3108417339","doi":"https://doi.org/10.1109/tip.2021.3089942","title":"Delving Deep Into Label Smoothing","display_name":"Delving Deep Into Label Smoothing","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3108417339","doi":"https://doi.org/10.1109/tip.2021.3089942","mag":"3108417339","pmid":"https://pubmed.ncbi.nlm.nih.gov/34166191"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2021.3089942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3089942","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2011.12562","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chang-Bin Zhang","orcid":"https://orcid.org/0000-0003-0043-8240"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang-Bin Zhang","raw_affiliation_strings":["TKLNDST, CS, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-0043-8240","affiliations":[{"raw_affiliation_string":"TKLNDST, CS, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Peng-Tao Jiang","orcid":"https://orcid.org/0000-0002-1786-4943"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng-Tao Jiang","raw_affiliation_strings":["TKLNDST, CS, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-1786-4943","affiliations":[{"raw_affiliation_string":"TKLNDST, CS, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qibin Hou","orcid":"https://orcid.org/0000-0002-8388-8708"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Qibin Hou","raw_affiliation_strings":["National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-8388-8708","affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yunchao Wei","orcid":"https://orcid.org/0000-0002-2812-8781"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunchao Wei","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2812-8781","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qi Han","orcid":null},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Han","raw_affiliation_strings":["TKLNDST, CS, Nankai University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TKLNDST, CS, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhen Li","orcid":null},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Li","raw_affiliation_strings":["TKLNDST, CS, Nankai University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TKLNDST, CS, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ming-Ming Cheng","orcid":"https://orcid.org/0000-0001-5550-8758"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming-Ming Cheng","raw_affiliation_strings":["TKLNDST, CS, Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-5550-8758","affiliations":[{"raw_affiliation_string":"TKLNDST, CS, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":20.2902,"has_fulltext":false,"cited_by_count":229,"citation_normalized_percentile":{"value":0.99524295,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"30","issue":null,"first_page":"5984","last_page":"5996"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.8278999924659729,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.8278999924659729,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.08730000257492065,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.007600000128149986,"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/smoothing","display_name":"Smoothing","score":0.8396000266075134},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7739999890327454},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5935999751091003},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5307999849319458},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48890000581741333},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.48260000348091125},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.43380001187324524},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4018000066280365}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.8396000266075134},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7739999890327454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6438000202178955},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.620199978351593},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5935999751091003},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5307999849319458},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.43380001187324524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41850000619888306},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4018000066280365},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3684999942779541},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30799999833106995},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2976999878883362},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2678000032901764},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26100000739097595},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2542000114917755}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2021.3089942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3089942","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:34166191","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34166191","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:arXiv.org:2011.12562","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.12562","pdf_url":"https://arxiv.org/pdf/2011.12562","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2011.12562","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2011.12562","pdf_url":"https://arxiv.org/pdf/2011.12562","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1349274172","display_name":null,"funder_award_id":"2018AAA0100400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3432882601","display_name":null,"funder_award_id":"61922046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6130512360","display_name":null,"funder_award_id":"63213090","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1514928307","https://openalex.org/W2031489346","https://openalex.org/W2068562306","https://openalex.org/W2108598243","https://openalex.org/W2138011018","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2289708887","https://openalex.org/W2328317224","https://openalex.org/W2345474290","https://openalex.org/W2512563520","https://openalex.org/W2533598788","https://openalex.org/W2549139847","https://openalex.org/W2598946096","https://openalex.org/W2616630373","https://openalex.org/W2731821979","https://openalex.org/W2752782242","https://openalex.org/W2765268259","https://openalex.org/W2791759999","https://openalex.org/W2883332448","https://openalex.org/W2883888092","https://openalex.org/W2884397828","https://openalex.org/W2901505625","https://openalex.org/W2902557560","https://openalex.org/W2903105043","https://openalex.org/W2904170036","https://openalex.org/W2928165649","https://openalex.org/W2944938209","https://openalex.org/W2951464224","https://openalex.org/W2963037989","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2963509340","https://openalex.org/W2964274690","https://openalex.org/W2967052791","https://openalex.org/W2976181893","https://openalex.org/W2979302305","https://openalex.org/W2981873476","https://openalex.org/W2981903848","https://openalex.org/W2982247743","https://openalex.org/W2982376094","https://openalex.org/W2982770724","https://openalex.org/W2987861506","https://openalex.org/W2987906097","https://openalex.org/W2990019157","https://openalex.org/W2990789488","https://openalex.org/W2991327923","https://openalex.org/W3005295611","https://openalex.org/W3023174223","https://openalex.org/W3034756453","https://openalex.org/W3034885317","https://openalex.org/W3092095626","https://openalex.org/W3100341797","https://openalex.org/W3113757710","https://openalex.org/W4300311439","https://openalex.org/W6637373629","https://openalex.org/W6638319203","https://openalex.org/W6638523607","https://openalex.org/W6640298173","https://openalex.org/W6640425456","https://openalex.org/W6678280073","https://openalex.org/W6728008421","https://openalex.org/W6729756640","https://openalex.org/W6739651123","https://openalex.org/W6743428213","https://openalex.org/W6745136726","https://openalex.org/W6750523955","https://openalex.org/W6751751081","https://openalex.org/W6754484989","https://openalex.org/W6756040250","https://openalex.org/W6762161020","https://openalex.org/W6762718338","https://openalex.org/W6763430915","https://openalex.org/W6763485134","https://openalex.org/W6765710127","https://openalex.org/W6785652829","https://openalex.org/W6787972765"],"related_works":[],"abstract_inverted_index":{"Label":[0,64],"smoothing":[1,146],"is":[2,30,151],"an":[3,62],"effective":[4],"regularization":[5],"tool":[6],"for":[7,80],"deep":[8],"neural":[9],"networks":[10],"(DNNs),":[11],"which":[12,68],"generates":[13,69],"soft":[14,58,70],"labels":[15,71,141],"by":[16],"applying":[17],"a":[18,88],"weighted":[19],"average":[20],"between":[21,93],"the":[22,26,35,74,77,81,94,108,112,118,128,134],"uniform":[23],"distribution":[24,92],"and":[25,41,97,124],"hard":[27],"label.":[28],"It":[29],"often":[31],"used":[32],"to":[33,51,54,100,139,143],"reduce":[34],"overfitting":[36],"problem":[37],"of":[38,76,136],"training":[39],"DNNs":[40],"further":[42],"improve":[43,117,133],"classification":[44,110,119],"performance.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49],"aim":[50],"investigate":[52],"how":[53],"generate":[55],"more":[56,89],"reliable":[57],"labels.":[59],"We":[60],"present":[61],"Online":[63],"Smoothing":[65],"(OLS)":[66],"strategy,":[67],"based":[72,106],"on":[73,107,121],"statistics":[75],"model":[78],"prediction":[79],"target":[82,95],"category.":[83],"The":[84,148],"proposed":[85,113,129],"OLS":[86],"constructs":[87],"reasonable":[90],"probability":[91],"categories":[96,99],"non-target":[98],"supervise":[101],"DNNs.":[102],"Experiments":[103],"demonstrate":[104],"that":[105],"same":[109],"models,":[111],"approach":[114],"can":[115,131],"effectively":[116],"performance":[120],"CIFAR-100,":[122],"ImageNet,":[123],"fine-grained":[125],"datasets.":[126],"Additionally,":[127],"method":[130],"significantly":[132],"robustness":[135],"DNN":[137],"models":[138],"noisy":[140],"compared":[142],"current":[144],"label":[145],"approaches.":[147],"source":[149],"code":[150],"available":[152],"at":[153],"our":[154],"project":[155],"page:":[156],"https://mmcheng.net/ols/.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":73},{"year":2024,"cited_by_count":60},{"year":2023,"cited_by_count":52},{"year":2022,"cited_by_count":31},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2020-12-07T00:00:00"}
