{"id":"https://openalex.org/W4402351732","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650017","title":"Self-supervised Benchmark Lottery on ImageNet: Do Marginal Improvements Translate to Improvements on Similar Datasets?","display_name":"Self-supervised Benchmark Lottery on ImageNet: Do Marginal Improvements Translate to Improvements on Similar Datasets?","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402351732","doi":"https://doi.org/10.1109/ijcnn60899.2024.10650017"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10650017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650017","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2501.15431","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008707729","display_name":"Utku \u00d6zbulak","orcid":"https://orcid.org/0000-0003-3084-6034"},"institutions":[{"id":"https://openalex.org/I4210132857","display_name":"Ghent University Global Campus","ror":"https://ror.org/041bygf77","country_code":"KR","type":"education","lineage":["https://openalex.org/I32597200","https://openalex.org/I4210132857"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Utku Ozbulak","raw_affiliation_strings":["Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea","institution_ids":["https://openalex.org/I4210132857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068577161","display_name":"Esla Timothy Anzaku","orcid":"https://orcid.org/0009-0005-7723-159X"},"institutions":[{"id":"https://openalex.org/I4210132857","display_name":"Ghent University Global Campus","ror":"https://ror.org/041bygf77","country_code":"KR","type":"education","lineage":["https://openalex.org/I32597200","https://openalex.org/I4210132857"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Esla Timothy Anzaku","raw_affiliation_strings":["Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea","institution_ids":["https://openalex.org/I4210132857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008856968","display_name":"Solha Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132857","display_name":"Ghent University Global Campus","ror":"https://ror.org/041bygf77","country_code":"KR","type":"education","lineage":["https://openalex.org/I32597200","https://openalex.org/I4210132857"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Solha Kang","raw_affiliation_strings":["Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea","institution_ids":["https://openalex.org/I4210132857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029555436","display_name":"Wesley De Neve","orcid":"https://orcid.org/0000-0002-8190-3839"},"institutions":[{"id":"https://openalex.org/I4210132857","display_name":"Ghent University Global Campus","ror":"https://ror.org/041bygf77","country_code":"KR","type":"education","lineage":["https://openalex.org/I32597200","https://openalex.org/I4210132857"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wesley De Neve","raw_affiliation_strings":["Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea","institution_ids":["https://openalex.org/I4210132857"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012688473","display_name":"Joris Vankerschaver","orcid":"https://orcid.org/0000-0002-5813-5659"},"institutions":[{"id":"https://openalex.org/I4210132857","display_name":"Ghent University Global Campus","ror":"https://ror.org/041bygf77","country_code":"KR","type":"education","lineage":["https://openalex.org/I32597200","https://openalex.org/I4210132857"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Joris Vankerschaver","raw_affiliation_strings":["Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ghent University Global Campus,Center for Biosystems and Biotech Data Science,Republic of Korea","institution_ids":["https://openalex.org/I4210132857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210132857"],"apc_list":null,"apc_paid":null,"fwci":0.2617,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53434837,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.8158197402954102},{"id":"https://openalex.org/keywords/lottery","display_name":"Lottery","score":0.8045215606689453},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7255654335021973},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6216373443603516},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5117452144622803},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0933900773525238},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09278473258018494},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0640454888343811}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8158197402954102},{"id":"https://openalex.org/C2777340749","wikidata":"https://www.wikidata.org/wiki/Q6684955","display_name":"Lottery","level":2,"score":0.8045215606689453},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7255654335021973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6216373443603516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5117452144622803},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0933900773525238},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09278473258018494},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0640454888343811},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10650017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10650017","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:arXiv.org:2501.15431","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.15431","pdf_url":"https://arxiv.org/pdf/2501.15431","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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"},{"id":"pmh:oai:archive.ugent.be:01KM4YJDS1DJS3ENTEZ1KG6QYR","is_oa":false,"landing_page_url":"https://biblio.ugent.be/publication/01KM4YJDS1DJS3ENTEZ1KG6QYR","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9798350359312","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2501.15431","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.15431","pdf_url":"https://arxiv.org/pdf/2501.15431","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402351732.pdf"},"referenced_works_count":78,"referenced_works":["https://openalex.org/W343636949","https://openalex.org/W1861492603","https://openalex.org/W2063971957","https://openalex.org/W2112796928","https://openalex.org/W2113896236","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2308529009","https://openalex.org/W2326925005","https://openalex.org/W2395579298","https://openalex.org/W2531327146","https://openalex.org/W2549139847","https://openalex.org/W2558661413","https://openalex.org/W2785325870","https://openalex.org/W2804935296","https://openalex.org/W2883725317","https://openalex.org/W2899771611","https://openalex.org/W2947707615","https://openalex.org/W2963420272","https://openalex.org/W2963470893","https://openalex.org/W2963542245","https://openalex.org/W2989457543","https://openalex.org/W2990873191","https://openalex.org/W2998702515","https://openalex.org/W3008526508","https://openalex.org/W3018265077","https://openalex.org/W3026414903","https://openalex.org/W3034781633","https://openalex.org/W3034942609","https://openalex.org/W3035524453","https://openalex.org/W3036224891","https://openalex.org/W3037492894","https://openalex.org/W3040572086","https://openalex.org/W3108807663","https://openalex.org/W3109684201","https://openalex.org/W3145450063","https://openalex.org/W3156669901","https://openalex.org/W3159481202","https://openalex.org/W3167014763","https://openalex.org/W3171007011","https://openalex.org/W3172456032","https://openalex.org/W3176276772","https://openalex.org/W3177096435","https://openalex.org/W4246193833","https://openalex.org/W4286695273","https://openalex.org/W4286851174","https://openalex.org/W4287724856","https://openalex.org/W4288024349","https://openalex.org/W4297808394","https://openalex.org/W4297918764","https://openalex.org/W4308831279","https://openalex.org/W4367000428","https://openalex.org/W4378464916","https://openalex.org/W6637373629","https://openalex.org/W6640425456","https://openalex.org/W6728622933","https://openalex.org/W6747899497","https://openalex.org/W6756040250","https://openalex.org/W6756444276","https://openalex.org/W6763468762","https://openalex.org/W6764990469","https://openalex.org/W6770152525","https://openalex.org/W6770196601","https://openalex.org/W6774314701","https://openalex.org/W6774908330","https://openalex.org/W6777265123","https://openalex.org/W6779602356","https://openalex.org/W6779997284","https://openalex.org/W6780616643","https://openalex.org/W6780666095","https://openalex.org/W6791742336","https://openalex.org/W6795754764","https://openalex.org/W6795782563","https://openalex.org/W6796630211","https://openalex.org/W6804355282","https://openalex.org/W6844194202","https://openalex.org/W6851949647","https://openalex.org/W6853115955"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Machine":[0],"learning":[1,60,87],"(ML)":[2],"research":[3,24],"strongly":[4],"relies":[5],"on":[6,75,78,105,118,123,137,150,157,208,225,250],"benchmarks":[7],"in":[8,55,94,109,177],"order":[9],"to":[10,41,121,147,228],"determine":[11],"the":[12,34,56,65,82,95,106,209,222,236,246],"relative":[13],"effectiveness":[14],"of":[15,22,30,58,85,98,199,238,248],"newly":[16,68],"proposed":[17,69,93],"models.":[18],"Recently,":[19],"a":[20,28,37,49,189,230,239],"number":[21,29,84],"prominent":[23],"effort":[25],"argued":[26],"that":[27,32,90,143,145,193,242],"models":[31,70,144,200,249],"improve":[33],"state-of-the-art":[35,161],"by":[36,44],"small":[38],"margin":[39],"tend":[40],"do":[42,129],"so":[43],"winning":[45],"what":[46],"they":[47],"call":[48,215],"\"benchmark":[50,223],"lottery\".":[51],"An":[52],"important":[53],"benchmark":[54],"field":[57],"machine":[59],"and":[61,141,166,181,196,227],"computer":[62],"vision":[63],"is":[64,205],"ImageNet":[66,107,119,139,151,210,226,252],"where":[67],"are":[71,169],"often":[72],"showcased":[73],"based":[74],"their":[76,172],"performance":[77,155,178,247],"this":[79,110],"dataset.":[80],"Given":[81],"large":[83],"self-supervised":[86],"(SSL)":[88],"frameworks":[89,136,162],"has":[91],"been":[92],"past":[96],"couple":[97],"years":[99],"each":[100],"coming":[101],"with":[102],"marginal":[103,116],"improvements":[104,117,122],"dataset,":[108],"work,":[111],"we":[112,131,191,234],"evaluate":[113],"whether":[114],"those":[115],"translate":[120],"similar":[124,158],"datasets":[125],"or":[126],"not.":[127],"To":[128,220],"so,":[130],"investigate":[132,235],"twelve":[133],"popular":[134],"SSL":[135],"five":[138],"variants":[140],"discover":[142],"seem":[146],"perform":[148],"well":[149],"may":[152],"experience":[153],"significant":[154],"declines":[156],"datasets.":[159,254],"Specifically,":[160],"such":[163],"as":[164],"DINO":[165],"Swav,":[167],"which":[168],"praised":[170],"for":[171,216],"performance,":[173],"exhibit":[174],"substantial":[175],"drops":[176],"while":[179],"MoCo":[180],"Barlow":[182],"Twins":[183],"displays":[184],"comparatively":[185],"good":[186,195],"results.":[187],"As":[188],"result,":[190],"argue":[192],"otherwise":[194],"desirable":[197],"properties":[198],"remain":[201],"hidden":[202],"when":[203],"benchmarking":[204,232],"only":[206],"performed":[207],"validation":[211],"set,":[212],"making":[213],"us":[214],"more":[217],"adequate":[218],"benchmarking.":[219],"avoid":[221],"lottery\"":[224],"ensure":[229],"fair":[231],"process,":[233],"usage":[237],"unified":[240],"metric":[241],"takes":[243],"into":[244],"account":[245],"other":[251],"variant":[253]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
