{"id":"https://openalex.org/W7128518495","doi":"https://doi.org/10.48550/arxiv.2602.08071","title":"ViT-5: Vision Transformers for The Mid-2020s","display_name":"ViT-5: Vision Transformers for The Mid-2020s","publication_year":2026,"publication_date":"2026-02-08","ids":{"openalex":"https://openalex.org/W7128518495","doi":"https://doi.org/10.48550/arxiv.2602.08071"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2602.08071","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125495945","display_name":"Feng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wang, Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048891976","display_name":"Sucheng Ren","orcid":"https://orcid.org/0000-0003-4730-8435"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Sucheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001604900","display_name":"Tiezheng Zhang","orcid":"https://orcid.org/0000-0002-2228-1822"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Tiezheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070935552","display_name":"Predrag Neskovic","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neskovic, Predrag","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120686838","display_name":"Anand Bhattad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhattad, Anand","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109737663","display_name":"Cihang Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Cihang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125500943","display_name":"Alan Yuille","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuille, Alan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5125495945"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":0.33869999647140503,"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":0.33869999647140503,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.13099999725818634,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.056299999356269836,"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/transformer","display_name":"Transformer","score":0.6395999789237976},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.41290000081062317},{"id":"https://openalex.org/keywords/headline","display_name":"Headline","score":0.40470001101493835},{"id":"https://openalex.org/keywords/upgrade","display_name":"Upgrade","score":0.4000000059604645},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.3630000054836273},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.35749998688697815},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.28870001435279846}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6395999789237976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6195999979972839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5041999816894531},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4302999973297119},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C2780615140","wikidata":"https://www.wikidata.org/wiki/Q920419","display_name":"Upgrade","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.35749998688697815},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2849999964237213},{"id":"https://openalex.org/C200220432","wikidata":"https://www.wikidata.org/wiki/Q7936208","display_name":"Vision science","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.2583000063896179},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25769999623298645},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.25029999017715454},{"id":"https://openalex.org/C194544171","wikidata":"https://www.wikidata.org/wiki/Q21105679","display_name":"Gating","level":2,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2602.08071","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2602.08071","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.08071","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:doi:10.48550/arxiv.2602.08071","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"work":[1],"presents":[2],"a":[3,28,45,91,111,134,143],"systematic":[4],"investigation":[5],"into":[6,99],"modernizing":[7],"Vision":[8,49,64],"Transformer":[9],"backbones":[10],"by":[11],"leveraging":[12],"architectural":[13],"advancements":[14],"from":[15],"the":[16,22],"past":[17],"five":[18],"years.":[19],"While":[20],"preserving":[21],"canonical":[23],"Attention-FFN":[24],"structure,":[25],"we":[26,52],"conduct":[27],"component-wise":[29],"refinement":[30],"involving":[31],"normalization,":[32],"activation":[33],"functions,":[34],"positional":[35],"encoding,":[36],"gating":[37],"mechanisms,":[38],"and":[39,69,123,128],"learnable":[40],"tokens.":[41],"These":[42],"updates":[43],"form":[44],"new":[46],"generation":[47,70],"of":[48],"Transformers,":[50],"which":[51],"call":[53],"ViT-5.":[54],"Extensive":[55],"experiments":[56],"demonstrate":[57],"that":[58],"ViT-5":[59,87,118,141],"consistently":[60],"outperforms":[61],"state-of-the-art":[62],"plain":[63],"Transformers":[65],"across":[66,131],"both":[67],"understanding":[68],"benchmarks.":[71],"On":[72],"ImageNet-1k":[73],"classification,":[74],"ViT-5-Base":[75],"reaches":[76],"84.2\\%":[77],"top-1":[78],"accuracy":[79],"under":[80],"comparable":[81],"compute,":[82],"exceeding":[83],"DeiT-III-Base":[84],"at":[85],"83.8\\%.":[86],"also":[88],"serves":[89],"as":[90],"stronger":[92],"backbone":[93],"for":[94,150],"generative":[95],"modeling:":[96],"when":[97],"plugged":[98],"an":[100],"SiT":[101],"diffusion":[102],"framework,":[103],"it":[104],"achieves":[105],"1.84":[106],"FID":[107],"versus":[108],"2.06":[109],"with":[110,137],"vanilla":[112,148],"ViT":[113,149],"backbone.":[114],"Beyond":[115],"headline":[116],"metrics,":[117],"exhibits":[119],"improved":[120],"representation":[121],"learning":[122],"favorable":[124],"spatial":[125],"reasoning":[126],"behavior,":[127],"transfers":[129],"reliably":[130],"tasks.":[132],"With":[133],"design":[135],"aligned":[136],"contemporary":[138],"foundation-model":[139],"practices,":[140],"offers":[142],"simple":[144],"drop-in":[145],"upgrade":[146],"over":[147],"mid-2020s":[151],"vision":[152],"backbones.":[153]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-02-11T00:00:00"}
