{"id":"https://openalex.org/W7138007354","doi":"https://doi.org/10.1609/aaai.v40i11.37839","title":"vMFCoOp: Towards Equilibrium on a Unified Hyperspherical Manifold for Prompting Biomedical VLMs","display_name":"vMFCoOp: Towards Equilibrium on a Unified Hyperspherical Manifold for Prompting Biomedical VLMs","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138007354","doi":"https://doi.org/10.1609/aaai.v40i11.37839"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i11.37839","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i11.37839","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i11.37839","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125766259","display_name":"Minye Shao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minye Shao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111201824","display_name":"Sihan Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sihan Guo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129649947","display_name":"Xinrun Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinrun Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129670945","display_name":"Xingyu Miao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xingyu Miao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129712475","display_name":"Haoran Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haoran Duan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129734383","display_name":"Yang Long","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Long","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19496755,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"11","first_page":"8851","last_page":"8859"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.28760001063346863,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.28760001063346863,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.2646999955177307,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.14409999549388885,"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/context","display_name":"Context (archaeology)","score":0.6607999801635742},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6078000068664551},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5679000020027161},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5157999992370605},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.38670000433921814},{"id":"https://openalex.org/keywords/unified-medical-language-system","display_name":"Unified Medical Language System","score":0.36660000681877136},{"id":"https://openalex.org/keywords/structured-prediction","display_name":"Structured prediction","score":0.34709998965263367},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.34119999408721924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.677299976348877},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6607999801635742},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6078000068664551},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5679000020027161},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5393000245094299},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5157999992370605},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.38670000433921814},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36820000410079956},{"id":"https://openalex.org/C69505689","wikidata":"https://www.wikidata.org/wiki/Q455338","display_name":"Unified Medical Language System","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.34709998965263367},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.3398999869823456},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33629998564720154},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32089999318122864},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.3165000081062317},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.30630001425743103},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2671999931335449},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i11.37839","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i11.37839","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i11.37839","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i11.37839","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-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":{"Recent":[0],"advances":[1],"in":[2,36,95,147,170],"context":[3,38],"optimization":[4,76],"(CoOp)":[5],"guided":[6],"by":[7,41],"large":[8],"language":[9],"model":[10,55,81],"(LLM)\u2013distilled":[11],"medical":[12,157,160],"semantic":[13,42,125],"priors":[14],"offer":[15],"a":[16,110,120],"scalable":[17],"alternative":[18],"to":[19,50,80,91,137],"manual":[20],"prompt":[21,34],"engineering":[22],"and":[23,46,54,99,130,142,163,173],"full":[24],"fine-tuning":[25],"for":[26],"adapting":[27],"biomedical":[28,97,140],"CLIP-based":[29],"vision-language":[30],"models":[31],"(VLMs).":[32],"However,":[33],"learning":[35],"this":[37],"is":[39],"challenged":[40],"misalignment":[43],"between":[44,127],"LLMs":[45,129],"CLIP":[47,131],"variants":[48],"due":[49],"divergent":[51],"training":[52],"corpora":[53],"architectures;":[56],"it":[57],"further":[58],"lacks":[59,77],"scalability":[60],"across":[61,155],"continuously":[62],"evolving":[63],"families":[64],"of":[65],"foundation":[66],"models.":[67],"More":[68],"critically,":[69],"pairwise":[70],"multimodal":[71],"alignment":[72],"via":[73,133],"conventional":[74],"Euclidean-space":[75],"the":[78],"capacity":[79],"unified":[82],"representations":[83],"or":[84],"apply":[85],"localized":[86],"geometric":[87],"constraints,":[88,150],"which":[89],"tends":[90],"amplify":[92],"modality":[93],"gaps":[94],"complex":[96],"imaging":[98,161],"destabilize":[100],"few-shot":[101,144],"adaptation.":[102],"To":[103],"address":[104],"these":[105],"challenges,":[106],"we":[107],"propose":[108],"vMFCoOp,":[109],"framework":[111],"that":[112],"inversely":[113],"estimates":[114],"von":[115],"Mises\u2013Fisher":[116],"(vMF)":[117],"distributions":[118],"on":[119],"shared":[121],"Hyperspherical":[122],"Manifold,":[123],"aligning":[124],"biases":[126],"arbitrary":[128],"backbones":[132],"Unified":[134],"Semantic":[135],"Anchors":[136],"achieve":[138],"robust":[139],"prompting":[141],"superior":[143],"classification.":[145],"Grounded":[146],"three":[148],"complementary":[149],"vMFCoOp":[151],"demonstrates":[152],"consistent":[153],"improvements":[154],"14":[156],"datasets,":[158],"12":[159],"modalities,":[162],"13":[164],"anatomical":[165],"regions,":[166],"outperforming":[167],"state-of-the-art":[168],"methods":[169],"accuracy,":[171],"generalization,":[172],"clinical":[174],"applicability.":[175]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-18T00:00:00"}
