{"id":"https://openalex.org/W7148514218","doi":"https://doi.org/10.48550/arxiv.2604.00243","title":"UCell: rethinking generalizability and scaling of bio-medical vision models","display_name":"UCell: rethinking generalizability and scaling of bio-medical vision models","publication_year":2026,"publication_date":"2026-03-31","ids":{"openalex":"https://openalex.org/W7148514218","doi":"https://doi.org/10.48550/arxiv.2604.00243"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.00243","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00243","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.2604.00243","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038958248","display_name":"Nicholas Kuang","orcid":"https://orcid.org/0000-0001-6665-6895"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kuang, Nicholas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132809578","display_name":"Vanessa Scalon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Scalon, Vanessa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132805228","display_name":"Ji Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Ji","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038958248"],"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.45559999346733093,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.45559999346733093,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":0.4262999892234802,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.028699999675154686,"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/generalizability-theory","display_name":"Generalizability theory","score":0.8608999848365784},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6065000295639038},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5839999914169312},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5407000184059143},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5127999782562256},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.5059999823570251},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4830999970436096},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4505999982357025}],"concepts":[{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.8608999848365784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6308000087738037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.613099992275238},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6065000295639038},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5839999914169312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5432999730110168},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5407000184059143},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5127999782562256},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.5059999823570251},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.4357999861240387},{"id":"https://openalex.org/C189474733","wikidata":"https://www.wikidata.org/wiki/Q917912","display_name":"Model building","level":2,"score":0.42820000648498535},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4244999885559082},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.41670000553131104},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C66153294","wikidata":"https://www.wikidata.org/wiki/Q899291","display_name":"CASP","level":4,"score":0.31929999589920044},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2619999945163727},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.00243","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00243","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.2604.00243","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.00243","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":[{"display_name":"Industry, innovation and infrastructure","score":0.5148620009422302,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"modern":[1,97],"deep":[2],"learning":[3],"field":[4],"is":[5,34,109,227],"a":[6,113,124,153,173,209,220],"scale-centric":[7],"one.":[8],"Larger":[9],"models":[10,20,82,91,146],"have":[11],"been":[12,84],"shown":[13],"to":[14,99,123,156],"consistently":[15],"perform":[16,100],"better":[17],"than":[18],"smaller":[19],"of":[21,27,39,62,76,80,112,145,175,205,212,223],"similar":[22,154],"architecture.":[23,127],"In":[24],"many":[25],"sub-domains":[26],"biomedical":[28],"research,":[29],"however,":[30],"the":[31,37,44,57,60,63,74,78,101,110,117,132,143,190,203],"model":[32,191],"scaling":[33],"bottlenecked":[35],"by":[36,96,207],"amount":[38],"available":[40,228],"training":[41],"data,":[42,178],"and":[43,50,151,187,201,214],"high":[45,53],"cost":[46],"associated":[47],"with":[48,89,92,152],"generating":[49],"validating":[51],"additional":[52],"quality":[54],"data.":[55,159],"Despite":[56],"practical":[58],"hurdle,":[59],"majority":[61],"ongoing":[64],"research":[65],"still":[66],"focuses":[67],"on":[68,135,181,184,219],"building":[69,90,192],"bigger":[70],"foundation":[71],"models,":[72],"whereas":[73],"alternative":[75],"improving":[77],"ability":[79],"small":[81,139,224],"has":[83],"under-explored.":[85],"Here":[86],"we":[87,162,199],"experiment":[88],"10-30M":[93],"parameters,":[94],"tiny":[95],"standards,":[98],"single-cell":[102,133],"segmentation":[103],"task.":[104],"An":[105],"important":[106],"design":[107],"choice":[108],"incorporation":[111],"recursive":[114],"structure":[115],"into":[116],"model's":[118],"forward":[119],"computation":[120],"graph,":[121],"leading":[122],"more":[125],"parameter-efficient":[126],"We":[128],"found":[129,163],"that":[130,164],"for":[131],"segmentation,":[134],"multiple":[136],"benchmarks,":[137],"our":[138],"model,":[140],"UCell,":[141],"matches":[142],"performance":[144],"10-20":[147],"times":[148],"its":[149],"size,":[150],"generalizability":[155],"unseen":[157],"out-of-domain":[158],"More":[160],"importantly,":[161],"ucell":[165,206],"can":[166],"be":[167],"trained":[168],"from":[169,193],"scratch":[170],"using":[171],"only":[172],"set":[174,222],"microscopy":[176],"imaging":[177],"without":[179],"relying":[180],"massive":[182],"pretraining":[183],"natural":[185],"images,":[186],"therefore":[188],"decouples":[189],"any":[194],"external":[195],"commercial":[196],"interests.":[197],"Finally,":[198],"examined":[200],"confirmed":[202],"adaptability":[204],"performing":[208],"wide":[210],"range":[211],"one-shot":[213],"few-shot":[215],"fine":[216],"tuning":[217],"experiments":[218],"diverse":[221],"datasets.":[225],"Implementation":[226],"at":[229],"https://github.com/jiyuuchc/ucell":[230]},"counts_by_year":[],"updated_date":"2026-04-03T16:44:17.987007","created_date":"2026-04-03T00:00:00"}