{"id":"https://openalex.org/W7143352661","doi":"https://doi.org/10.48550/arxiv.2603.26356","title":"From Pen to Pixel: Translating Hand-Drawn Plots into Graphical APIs via a Novel Benchmark and Efficient Adapter","display_name":"From Pen to Pixel: Translating Hand-Drawn Plots into Graphical APIs via a Novel Benchmark and Efficient Adapter","publication_year":2026,"publication_date":"2026-03-27","ids":{"openalex":"https://openalex.org/W7143352661","doi":"https://doi.org/10.48550/arxiv.2603.26356"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.26356","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26356","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.2603.26356","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130984513","display_name":"Zhenghao Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu, Zhenghao","raw_affiliation_strings":["School of Big Data and Software Engineering, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data and Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009186984","display_name":"Mengning Yang","orcid":"https://orcid.org/0000-0003-2320-1844"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang, Mengning","raw_affiliation_strings":["School of Big Data and Software Engineering, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Big Data and Software Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158842170"],"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":0.4278999865055084,"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":0.4278999865055084,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.193900004029274,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.051600001752376556,"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/plot","display_name":"Plot (graphics)","score":0.8680999875068665},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5478000044822693},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4943000078201294},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4941999912261963},{"id":"https://openalex.org/keywords/adapter","display_name":"Adapter (computing)","score":0.4878000020980835},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.38100001215934753},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.36910000443458557}],"concepts":[{"id":"https://openalex.org/C167651023","wikidata":"https://www.wikidata.org/wiki/Q1474611","display_name":"Plot (graphics)","level":2,"score":0.8680999875068665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7843000292778015},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5478000044822693},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4943000078201294},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4941999912261963},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.4878000020980835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44999998807907104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43479999899864197},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.3431999981403351},{"id":"https://openalex.org/C31462909","wikidata":"https://www.wikidata.org/wiki/Q1045782","display_name":"Scatter plot","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32850000262260437},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.27810001373291016},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.26356","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26356","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.2603.26356","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.26356","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":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.4216330647468567}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"plots":[1,23],"play":[2],"a":[3,108,175],"critical":[4],"role":[5],"in":[6,145],"modern":[7],"data":[8],"visualization":[9],"and":[10,18,63,77,97,104,135,142,155,169,187,208],"analysis,":[11],"Plot2API":[12,40,70],"is":[13],"launched":[14],"to":[15,61,84,93,114,127,179,183,192],"help":[16],"non-experts":[17,62,103],"beginners":[19],"create":[20],"their":[21],"desired":[22],"by":[24,33],"directly":[25],"recommending":[26],"graphical":[27,119],"APIs":[28,87],"from":[29,140],"reference":[30],"plot":[31,49,55,75,90,110,124],"images":[32,56,76,91],"neural":[34],"networks.":[35],"However,":[36],"previous":[37],"works":[38],"on":[39,44,73],"have":[41],"primarily":[42],"focused":[43],"the":[45,53,94,116,129,153,181,194,204,209],"recommendation":[46],"for":[47,88,122,152,166],"standard":[48,74],"images,":[50],"while":[51],"overlooking":[52],"hand-drawn":[54,89,109,123],"that":[57,150],"are":[58],"more":[59],"accessible":[60],"beginners.":[64],"To":[65,101],"make":[66],"matters":[67],"worse,":[68],"both":[69,203],"models":[71,82],"trained":[72],"powerful":[78],"multi-modal":[79],"large":[80],"language":[81,168],"struggle":[83],"effectively":[85],"recommend":[86],"due":[92],"domain":[95],"gap":[96],"lack":[98],"of":[99,118,132,157,196,206,211],"expertise.":[100],"facilitate":[102],"beginners,":[105],"we":[106,147],"introduce":[107],"dataset":[111],"named":[112],"HDpy-13":[113,207],"improve":[115,180],"performance":[117],"API":[120],"recommendations":[121],"images.":[125],"Additionally,":[126],"alleviate":[128],"considerable":[130],"strain":[131],"parameter":[133],"growth":[134],"computational":[136],"resource":[137],"costs":[138],"arising":[139],"multi-domain":[141],"multi-language":[143],"challenges":[144],"Plot2API,":[146],"propose":[148],"Plot-Adapter":[149,173],"allows":[151],"training":[154],"storage":[156],"separate":[158],"adapters":[159],"rather":[160],"than":[161],"requiring":[162],"an":[163],"entire":[164],"model":[165],"each":[167],"domain.":[170],"In":[171],"particular,":[172],"incorporates":[174],"lightweight":[176],"CNN":[177],"block":[178],"ability":[182],"capture":[184],"local":[185],"features":[186],"implements":[188],"projection":[189],"matrix":[190],"sharing":[191],"reduce":[193],"number":[195],"fine-tuning":[197],"parameters":[198],"further.":[199],"Experimental":[200],"results":[201],"demonstrate":[202],"effectiveness":[205],"efficiency":[210],"Plot-Adapter.":[212]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-31T00:00:00"}
