{"id":"https://openalex.org/W7134989245","doi":"https://doi.org/10.48550/arxiv.2603.08930","title":"Using Vision Language Foundation Models to Generate Plant Simulation Configurations via In-Context Learning","display_name":"Using Vision Language Foundation Models to Generate Plant Simulation Configurations via In-Context Learning","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134989245","doi":"https://doi.org/10.48550/arxiv.2603.08930"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.08930","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08930","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.2603.08930","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048969131","display_name":"Heesup Yun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yun, Heesup","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128775890","display_name":"Isaac Kazuo Uyehara","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Uyehara, Isaac Kazuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119248971","display_name":"Earl Ranario","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ranario, Earl","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128714720","display_name":"Lars Lundqvist","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lundqvist, Lars","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013340604","display_name":"Christine Diepenbrock","orcid":"https://orcid.org/0000-0001-8411-0343"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Diepenbrock, Christine H.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008008876","display_name":"Brian N. Bailey","orcid":"https://orcid.org/0000-0003-1919-2324"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bailey, Brian N.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128699786","display_name":"J. Mason Earles","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Earles, J. Mason","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/T10616","display_name":"Smart Agriculture and AI","score":0.6337000131607056,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.6337000131607056,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12093","display_name":"Greenhouse Technology and Climate Control","score":0.0949999988079071,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.0738999992609024,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/json","display_name":"JSON","score":0.8657000064849854},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5022000074386597},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4699999988079071},{"id":"https://openalex.org/keywords/plot","display_name":"Plot (graphics)","score":0.45260000228881836},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.40529999136924744},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.34470000863075256},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.3393000066280365},{"id":"https://openalex.org/keywords/plant-disease","display_name":"Plant disease","score":0.3005000054836273}],"concepts":[{"id":"https://openalex.org/C2780416260","wikidata":"https://www.wikidata.org/wiki/Q2063","display_name":"JSON","level":2,"score":0.8657000064849854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7329000234603882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5356000065803528},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5022000074386597},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.476500004529953},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4699999988079071},{"id":"https://openalex.org/C167651023","wikidata":"https://www.wikidata.org/wiki/Q1474611","display_name":"Plot (graphics)","level":2,"score":0.45260000228881836},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.34470000863075256},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3393000066280365},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33640000224113464},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30550000071525574},{"id":"https://openalex.org/C3019235130","wikidata":"https://www.wikidata.org/wiki/Q188956","display_name":"Plant disease","level":2,"score":0.3005000054836273},{"id":"https://openalex.org/C20136886","wikidata":"https://www.wikidata.org/wiki/Q749647","display_name":"Interoperability","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.29249998927116394},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C82789328","wikidata":"https://www.wikidata.org/wiki/Q922585","display_name":"Orthophoto","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C2778597888","wikidata":"https://www.wikidata.org/wiki/Q172169","display_name":"3D city models","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.08930","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08930","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.2603.08930","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08930","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":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.7413442134857178}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3,52,80,154,164,202],"synthetic":[4,81],"benchmark":[5],"to":[6,66,139,190,193],"evaluate":[7],"the":[8,87,102,169,180,187],"performance":[9,136],"of":[10,182],"vision":[11],"language":[12],"models":[13,26,103],"(VLMs)":[14],"in":[15,35,71,212],"generating":[16],"plant":[17,25,91,128,199],"simulation":[18,69],"configurations":[19,197],"for":[20,31,46,198,205,209],"digital":[21,210],"twins.":[22],"While":[23],"functional-structural":[24],"(FSPMs)":[27],"are":[28,150],"useful":[29],"tools":[30],"simulating":[32],"biophysical":[33,112],"processes":[34],"agricultural":[36],"environments,":[37],"their":[38,174],"high":[39],"complexity":[40],"and":[41,63,100,111,124,130,159],"low":[42],"throughput":[43],"create":[44],"bottlenecks":[45],"deployment":[47],"at":[48],"scale.":[49],"We":[50],"propose":[51],"novel":[53],"approach":[54],"that":[55,117],"leverages":[56],"state-of-the-art":[57],"open-source":[58],"VLMs":[59,119,192],"--":[60,65],"Gemma":[61],"3":[62],"Qwen3-VL":[64],"directly":[67],"generate":[68,194],"parameters":[70,126],"JSON":[72,107,196],"format":[73],"from":[74],"drone-based":[75],"remote":[76],"sensing":[77],"images.":[78],"Using":[79],"cowpea":[82],"plot":[83],"dataset":[84,145,158],"generated":[85],"via":[86],"Helios":[88],"3D":[89,207],"procedural":[90],"generation":[92],"library,":[93],"we":[94],"tested":[95],"five":[96],"in-context":[97],"learning":[98],"methods":[99],"evaluated":[101],"across":[104],"three":[105],"categories:":[106],"integrity,":[108],"geometric":[109],"evaluations,":[110],"evaluations.":[113],"Our":[114],"results":[115],"show":[116],"while":[118],"can":[120],"interpret":[121],"structural":[122,195],"metadata":[123],"estimate":[125],"like":[127],"count":[129],"sun":[131],"azimuth,":[132],"they":[133],"often":[134],"exhibit":[135],"degradation":[137],"due":[138],"contextual":[140,177],"bias":[141],"or":[142],"rely":[143],"on":[144,153,176],"means":[146],"when":[147],"visual":[148],"cues":[149],"insufficient.":[151],"Validation":[152],"real-world":[155],"drone":[156],"orthophoto":[157],"an":[160],"ablation":[161],"study":[162,189],"using":[163],"blind":[165],"baseline":[166],"further":[167],"characterize":[168],"models'":[170],"reasoning":[171],"capabilities":[172],"versus":[173],"reliance":[175],"priors.":[178],"To":[179],"best":[181],"our":[183],"knowledge,":[184],"this":[185],"is":[186],"first":[188],"utilize":[191],"simulations,":[200],"providing":[201],"scalable":[203],"framework":[204],"reconstruction":[206],"plots":[208],"twin":[211],"agriculture.":[213]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-12T00:00:00"}