{"id":"https://openalex.org/W7154231618","doi":"https://doi.org/10.48550/arxiv.2604.09757","title":"MedLVR: Latent Visual Reasoning for Reliable Medical Visual Question Answering","display_name":"MedLVR: Latent Visual Reasoning for Reliable Medical Visual Question Answering","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154231618","doi":"https://doi.org/10.48550/arxiv.2604.09757"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09757","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09757","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09757","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133600217","display_name":"Suyang Xi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xi, Suyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133560859","display_name":"Songtao Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Songtao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111304741","display_name":"Yuxiang Lai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Yuxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133610660","display_name":"Wangyun Dan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dan, Wangyun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133553235","display_name":"Yaqi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yaqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071213321","display_name":"Shansong Wang","orcid":"https://orcid.org/0000-0003-4208-2035"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shansong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5024697319","display_name":"Xiaofeng Yang","orcid":"https://orcid.org/0000-0001-5012-5651"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Xiaofeng","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":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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.991100013256073,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.991100013256073,"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":0.0031999999191612005,"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/T10028","display_name":"Topic Modeling","score":0.0007999999797903001,"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/inference","display_name":"Inference","score":0.6096000075340271},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.5999000072479248},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5666000247001648},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3919999897480011},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.3334999978542328},{"id":"https://openalex.org/keywords/deductive-reasoning","display_name":"Deductive reasoning","score":0.31949999928474426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7175999879837036},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6096000075340271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.609000027179718},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.5999000072479248},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5666000247001648},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4041000008583069},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3919999897480011},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C97364631","wikidata":"https://www.wikidata.org/wiki/Q484284","display_name":"Deductive reasoning","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.30399999022483826},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C206588197","wikidata":"https://www.wikidata.org/wiki/Q846574","display_name":"Reuse","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.251800000667572},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09757","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09757","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09757","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09757","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":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4743807315826416}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Medical":[0],"vision--language":[1],"models":[2],"(VLMs)":[3],"have":[4],"shown":[5],"strong":[6],"potential":[7],"for":[8,196],"medical":[9,161,207],"visual":[10,50,65,72,111,119,190,200],"question":[11],"answering":[12],"(VQA),":[13],"yet":[14],"their":[15],"reasoning":[16,66,91,148,170,191],"remains":[17],"largely":[18],"text-centric:":[19],"images":[20],"are":[21],"encoded":[22],"once":[23],"as":[24,100],"static":[25,58],"context,":[26],"and":[27,107,140,149,158,172,202],"subsequent":[28],"inference":[29],"is":[30,36],"dominated":[31],"by":[32,96],"language.":[33],"This":[34],"paradigm":[35],"fundamentally":[37],"limited":[38],"in":[39,57],"clinical":[40],"scenarios,":[41],"where":[42],"accurate":[43],"answers":[44],"often":[45],"depend":[46],"on":[47,82,156],"subtle,":[48],"localized":[49],"evidence":[51,73,112,201],"that":[52,68,165,188],"cannot":[53],"be":[54],"reliably":[55],"preserved":[56],"embeddings.":[59],"We":[60],"propose":[61],"\\textsc{MedLVR},":[62],"a":[63,88,123],"latent":[64,90,102,133,147,189],"framework":[67],"introduces":[69],"an":[70,193],"explicit":[71],"state":[74],"into":[75],"autoregressive":[76],"decoding.":[77],"Instead":[78],"of":[79,109,128,206],"relying":[80],"solely":[81],"text-based":[83],"intermediate":[84],"reasoning,":[85],"\\textsc{MedLVR}":[86,166],"interleaves":[87],"short":[89],"segment":[92],"within":[93],"the":[94,174,178,204],"decoder":[95],"reusing":[97],"hidden":[98],"states":[99,134],"continuous":[101],"steps,":[103],"enabling":[104],"iterative":[105],"preservation":[106],"refinement":[108],"query-relevant":[110],"before":[113],"answer":[114,150],"generation.":[115],"To":[116],"support":[117],"effective":[118,194],"supervision,":[120],"we":[121],"adopt":[122],"two-stage":[124],"training":[125],"strategy:":[126],"region":[127],"interest":[129],"(ROI)-supervised":[130],"fine-tuning":[131],"aligns":[132],"with":[135],"clinically":[136],"relevant":[137,199],"image":[138],"evidence,":[139],"Visual-Latent":[141],"Policy":[142],"Optimization":[143],"(VLPO)":[144],"further":[145],"optimizes":[146],"generation":[151],"under":[152],"outcome-level":[153],"rewards.":[154],"Experiments":[155],"OmniMedVQA":[157],"five":[159],"external":[160],"VQA":[162],"benchmarks":[163],"show":[164,187],"consistently":[167],"outperforms":[168],"recent":[169],"baselines":[171],"improves":[173],"average":[175],"score":[176],"over":[177],"Qwen2.5-VL-7B":[179],"backbone":[180],"from":[181],"48.3\\%":[182],"to":[183],"53.4\\%.":[184],"These":[185],"results":[186],"provides":[192],"mechanism":[195],"preserving":[197],"diagnostically":[198],"improving":[203],"reliability":[205],"VQA.":[208]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}
