{"id":"https://openalex.org/W7148849266","doi":"https://doi.org/10.48550/arxiv.2604.01987","title":"Curia-2: Scaling Self-Supervised Learning for Radiology Foundation Models","display_name":"Curia-2: Scaling Self-Supervised Learning for Radiology Foundation Models","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7148849266","doi":"https://doi.org/10.48550/arxiv.2604.01987"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01987","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01987","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.01987","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063633079","display_name":"Antoine Saporta","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Saporta, Antoine","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132855935","display_name":"Baptiste Callard","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Callard, Baptiste","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046767053","display_name":"Corentin Dancette","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dancette, Corentin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098823454","display_name":"Julien Khlaut","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Khlaut, Julien","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016868273","display_name":"Charles Corbi\u00e8re","orcid":"https://orcid.org/0000-0001-8024-7553"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Corbi\u00e8re, Charles","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132897832","display_name":"Leo Butsanets","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Butsanets, Leo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100033041","display_name":"Amaury Prat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prat, Amaury","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5103247659","display_name":"Pierre Manceron","orcid":"https://orcid.org/0000-0002-2970-973X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manceron, Pierre","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5063633079"],"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/T10036","display_name":"Advanced Neural Network Applications","score":0.2768999934196472,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.2768999934196472,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.12330000102519989,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.07559999823570251,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5519999861717224},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.45019999146461487},{"id":"https://openalex.org/keywords/restructuring","display_name":"Restructuring","score":0.43149998784065247},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.4302000105381012},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.4203000068664551},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.41019999980926514},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.38530001044273376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.636900007724762},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5519999861717224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5016000270843506},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.45019999146461487},{"id":"https://openalex.org/C45237549","wikidata":"https://www.wikidata.org/wiki/Q1376796","display_name":"Restructuring","level":2,"score":0.43149998784065247},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.4302000105381012},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.38530001044273376},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3151000142097473},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.28940001130104065},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C190892606","wikidata":"https://www.wikidata.org/wiki/Q3512464","display_name":"Radiological weapon","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C204983608","wikidata":"https://www.wikidata.org/wiki/Q2111958","display_name":"Productivity","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C2777601897","wikidata":"https://www.wikidata.org/wiki/Q3409113","display_name":"Presentation (obstetrics)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01987","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01987","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":"doi:10.48550/arxiv.2604.01987","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01987","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,78],"rapid":[1],"growth":[2],"of":[3,10,29,75,104],"medical":[4],"imaging":[5],"has":[6],"fueled":[7],"the":[8,16,27,53,63,73,83,102],"development":[9],"Foundation":[11],"Models":[12],"(FMs)":[13],"to":[14,32,41,70,86,145,162],"reduce":[15],"growing,":[17],"unsustainable":[18],"workload":[19],"on":[20,139,148],"radiologists.":[21],"While":[22],"recent":[23],"FMs":[24,138],"have":[25],"shown":[26],"power":[28],"large-scale":[30],"pre-training":[31,65],"CT":[33,95],"and":[34,67,96,109,124,142],"MRI":[35,97],"analysis,":[36],"there":[37],"remains":[38],"significant":[39],"room":[40],"optimize":[42],"how":[43],"these":[44,105],"models":[45,106,123,147],"learn":[46],"from":[47],"complex":[48,150],"radiological":[49,76],"volumes.":[50],"Building":[51],"upon":[52],"Curia":[54],"framework,":[55],"this":[56],"work":[57],"introduces":[58],"Curia-2,":[59],"which":[60],"significantly":[61],"improves":[62],"original":[64],"strategy":[66],"representation":[68],"quality":[69],"better":[71],"capture":[72],"specificities":[74],"data.":[77],"proposed":[79],"methodology":[80],"enables":[81],"scaling":[82],"architecture":[84],"up":[85],"billion-parameter":[87],"Vision":[88],"Transformers,":[89],"marking":[90],"a":[91,116,125],"first":[92],"for":[93,120,128],"multi-modal":[94],"FMs.":[98],"Furthermore,":[99],"we":[100],"formalize":[101],"evaluation":[103],"by":[107],"extending":[108],"restructuring":[110],"CuriaBench":[111],"into":[112],"two":[113],"distinct":[114],"tracks:":[115],"2D":[117],"track":[118,127],"tailored":[119],"slice-based":[121],"vision":[122],"3D":[126],"volumetric":[129],"benchmarking.":[130],"Our":[131],"results":[132],"demonstrate":[133],"that":[134],"Curia-2":[135],"outperforms":[136],"all":[137],"vision-focused":[140],"tasks":[141,151],"fairs":[143],"competitively":[144],"vision-language":[146],"clinically":[149],"such":[152],"as":[153],"finding":[154],"detection.":[155],"Weights":[156],"will":[157],"be":[158],"made":[159],"publicly":[160],"available":[161],"foster":[163],"further":[164],"research.":[165]},"counts_by_year":[],"updated_date":"2026-04-04T06:15:33.020886","created_date":"2026-04-04T00:00:00"}