{"id":"https://openalex.org/W7138942654","doi":"https://doi.org/10.48550/arxiv.2603.16057","title":"Toward Reliable Scientific Visualization Pipeline Construction with Structure-Aware Retrieval-Augmented LLMs","display_name":"Toward Reliable Scientific Visualization Pipeline Construction with Structure-Aware Retrieval-Augmented LLMs","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7138942654","doi":"https://doi.org/10.48550/arxiv.2603.16057"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.16057","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16057","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.16057","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129987049","display_name":"Guanghui Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Guanghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129876217","display_name":"Zhe Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Zhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130029159","display_name":"Yu Dong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075178545","display_name":"Guan Li","orcid":"https://orcid.org/0000-0001-6436-3650"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Guan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5039874476","display_name":"Guihua Shan","orcid":"https://orcid.org/0000-0002-8283-2278"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan, GuiHua","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/T10799","display_name":"Data Visualization and Analytics","score":0.4560000002384186,"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/T10799","display_name":"Data Visualization and Analytics","score":0.4560000002384186,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.43209999799728394,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.01759999990463257,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/visualization","display_name":"Visualization","score":0.8499000072479248},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.7354000210762024},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7027000188827515},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.5677000284194946},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5374000072479248},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.5302000045776367},{"id":"https://openalex.org/keywords/scientific-visualization","display_name":"Scientific visualization","score":0.4772000014781952}],"concepts":[{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.8499000072479248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7781000137329102},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.7354000210762024},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7027000188827515},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.5677000284194946},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.5302000045776367},{"id":"https://openalex.org/C59740354","wikidata":"https://www.wikidata.org/wiki/Q2737866","display_name":"Scientific visualization","level":3,"score":0.4772000014781952},{"id":"https://openalex.org/C175309249","wikidata":"https://www.wikidata.org/wiki/Q725864","display_name":"Pipeline transport","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4106999933719635},{"id":"https://openalex.org/C4379982","wikidata":"https://www.wikidata.org/wiki/Q1273511","display_name":"Software visualization","level":5,"score":0.39980000257492065},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.38029998540878296},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.36250001192092896},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.35910001397132874},{"id":"https://openalex.org/C185578843","wikidata":"https://www.wikidata.org/wiki/Q10609775","display_name":"Information visualization","level":3,"score":0.32499998807907104},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.302700012922287},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C14669888","wikidata":"https://www.wikidata.org/wiki/Q4014850","display_name":"Creative visualization","level":3,"score":0.26739999651908875},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.16057","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16057","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2603.16057","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16057","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.42505940794944763}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Scientific":[0],"visualization":[1,28,44,62,72,108,175],"pipelines":[2,29],"encode":[3],"domain-specific":[4,149],"procedural":[5],"knowledge":[6],"with":[7],"strict":[8],"execution":[9,97],"dependencies,":[10],"making":[11],"their":[12],"construction":[13],"sensitive":[14],"to":[15,139,166],"missing":[16],"stages,":[17],"incorrect":[18],"operator":[19],"usage,":[20],"or":[21],"improper":[22],"ordering.":[23],"Thus,":[24],"generating":[25],"executable":[26],"scientific":[27,61,107],"from":[30],"natural-language":[31],"descriptions":[32],"remains":[33],"challenging":[34],"for":[35,132],"large":[36],"language":[37],"models,":[38],"particularly":[39],"in":[40,114],"web-based":[41,71],"environments":[42],"where":[43],"authoring":[45],"relies":[46],"on":[47,66],"explicit":[48],"code-level":[49],"pipeline":[50,63,117,153],"assembly.":[51],"In":[52],"this":[53,124],"work,":[54],"we":[55,126],"investigate":[56],"the":[57,101,133],"reliability":[58,113],"of":[59,116,135,173],"LLM-based":[60],"generation,":[64],"focusing":[65],"vtk.js":[67,84],"as":[68,87,130],"a":[69,76,141],"representative":[70],"library.":[73],"We":[74,99,159],"propose":[75],"structure-aware":[77],"retrieval-augmented":[78],"generation":[79],"workflow":[80,103],"that":[81,147],"provides":[82],"pipeline-aligned":[83],"code":[85],"examples":[86],"contextual":[88],"guidance,":[89],"supporting":[90],"correct":[91],"module":[92],"selection,":[93],"parameter":[94],"configuration,":[95],"and":[96,110,119,155,170],"order.":[98],"evaluate":[100],"proposed":[102],"across":[104],"multiple":[105],"multi-stage":[106],"tasks":[109],"LLMs,":[111],"measuring":[112],"terms":[115],"executability":[118,154],"human":[120],"correction":[121,128,157],"effort.":[122],"To":[123],"end,":[125],"introduce":[127],"cost":[129],"metric":[131],"amount":[134],"manual":[136],"intervention":[137],"required":[138],"obtain":[140],"valid":[142],"pipeline.":[143],"Our":[144],"results":[145],"show":[146],"structured,":[148],"context":[150],"substantially":[151],"improves":[152],"reduces":[156],"cost.":[158],"additionally":[160],"provide":[161],"an":[162],"interactive":[163],"analysis":[164],"interface":[165],"support":[167],"human-in-the-loop":[168],"inspection":[169],"systematic":[171],"evaluation":[172],"generated":[174],"pipelines.":[176]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-20T00:00:00"}
