{"id":"https://openalex.org/W7148652874","doi":"https://doi.org/10.48550/arxiv.2604.01915","title":"Enhancing Medical Visual Grounding via Knowledge-guided Spatial Prompts","display_name":"Enhancing Medical Visual Grounding via Knowledge-guided Spatial Prompts","publication_year":2026,"publication_date":"2026-04-02","ids":{"openalex":"https://openalex.org/W7148652874","doi":"https://doi.org/10.48550/arxiv.2604.01915"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.01915","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01915","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.2604.01915","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132845311","display_name":"Yifan Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Yifan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132878209","display_name":"Tao Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132919275","display_name":"Yi Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132845553","display_name":"Ke Zou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zou, Ke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132859166","display_name":"Yizhe Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yizhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132834760","display_name":"Huazhu Fu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Huazhu","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":0.9316999912261963,"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":0.9316999912261963,"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":0.018200000748038292,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.007400000002235174,"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/perspective","display_name":"Perspective (graphical)","score":0.616100013256073},{"id":"https://openalex.org/keywords/visual-reasoning","display_name":"Visual reasoning","score":0.5814999938011169},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5440000295639038},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.43529999256134033},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.43050000071525574},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4052000045776367},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.38190001249313354},{"id":"https://openalex.org/keywords/visual-perception","display_name":"Visual perception","score":0.35339999198913574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6812999844551086},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.616100013256073},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.5814999938011169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5723000168800354},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5440000295639038},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.43529999256134033},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.43050000071525574},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4052000045776367},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3885999917984009},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.38190001249313354},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.35339999198913574},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33899998664855957},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C111370547","wikidata":"https://www.wikidata.org/wiki/Q7451120","display_name":"Sensory cue","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.29190000891685486},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.2870999872684479},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C168993435","wikidata":"https://www.wikidata.org/wiki/Q6501125","display_name":"Ground","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C155911833","wikidata":"https://www.wikidata.org/wiki/Q3817354","display_name":"Spatial intelligence","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2660999894142151},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C88626702","wikidata":"https://www.wikidata.org/wiki/Q1128903","display_name":"Continuation","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.01915","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01915","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.2604.01915","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.01915","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":[{"score":0.7861437797546387,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Medical":[0],"Visual":[1],"Grounding":[2],"(MVG)":[3],"aims":[4],"to":[5,26,48,124],"identify":[6],"diagnostically":[7],"relevant":[8],"phrases":[9],"from":[10,68],"free-text":[11],"radiology":[12],"reports":[13],"and":[14,72,77,120,136,166,175],"localize":[15],"their":[16,40],"corresponding":[17],"regions":[18],"in":[19,84,164,168],"medical":[20,104],"images,":[21],"providing":[22],"interpretable":[23],"visual":[24,138],"evidence":[25],"support":[27],"clinical":[28],"decision-making.":[29],"Although":[30],"recent":[31],"Vision-Language":[32],"Models":[33],"(VLMs)":[34],"exhibit":[35],"promising":[36],"multimodal":[37],"reasoning":[38,144],"ability,":[39],"grounding":[41],"remains":[42],"insufficient":[43],"spatial":[44,89],"precision,":[45],"largely":[46],"due":[47],"a":[49,75,96,111],"lack":[50],"of":[51,162,182],"explicit":[52],"localization":[53],"priors":[54],"when":[55],"relying":[56],"solely":[57],"on":[58,148],"latent":[59],"embeddings.":[60],"In":[61],"this":[62,66],"work,":[63],"we":[64,94],"analyze":[65],"limitation":[67],"an":[69],"attention":[70,79,113],"perspective":[71],"propose":[73],"KnowMVG,":[74],"Knowledge-prior":[76],"global-local":[78,112],"enhancement":[80],"framework":[81],"for":[82],"MVG":[83,150],"VLMs":[85],"that":[86,100,114,153],"explicitly":[87],"strengthens":[88],"awareness":[90],"during":[91],"decoding.":[92],"Specifically,":[93],"present":[95],"knowledge-enhanced":[97],"prompting":[98],"strategy":[99],"encodes":[101],"phrase":[102],"related":[103],"knowledge":[105],"into":[106],"compact":[107],"embeddings,":[108],"together":[109],"with":[110],"jointly":[115],"leverages":[116],"coarse":[117],"global":[118],"information":[119],"refined":[121],"local":[122],"cues":[123],"guide":[125],"precise":[126],"region":[127],"localization.":[128,129],"This":[130],"design":[131],"bridges":[132],"high-level":[133],"semantic":[134],"understanding":[135],"fine-grained":[137],"perception":[139],"without":[140],"introducing":[141],"extra":[142],"textual":[143],"overhead.":[145],"Extensive":[146],"experiments":[147],"four":[149],"benchmarks":[151],"demonstrate":[152],"our":[154],"KnowMVG":[155],"consistently":[156],"outperforms":[157],"existing":[158],"approaches,":[159],"achieving":[160],"gains":[161],"3.0%":[163],"AP50":[165],"2.6%":[167],"mIoU":[169],"over":[170],"prior":[171],"state-of-the-art":[172],"methods.":[173],"Qualitative":[174],"ablation":[176],"studies":[177],"further":[178],"validate":[179],"the":[180],"effectiveness":[181],"each":[183],"component.":[184]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-04T00:00:00"}