{"id":"https://openalex.org/W7112842953","doi":null,"title":"Schematic Network Extraction using Multimodal Generative Models : A Performance Evaluation of GPT-4o","display_name":"Schematic Network Extraction using Multimodal Generative Models : A Performance Evaluation of GPT-4o","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7112842953"},"language":"en","primary_location":{"id":"pmh:oai:DiVA.org:umu-245829","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-245829","pdf_url":"https://umu.diva-portal.org/smash/get/diva2:2008968/FULLTEXT01","source":{"id":"https://openalex.org/S4306400361","display_name":"DiVA at Ume\u00e5 University (Ume\u00e5 University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I90267481","host_organization_name":"Ume\u00e5 University","host_organization_lineage":["https://openalex.org/I90267481"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bachelorThesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://umu.diva-portal.org/smash/get/diva2:2008968/FULLTEXT01","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Olofsson, Lisa","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Olofsson, Lisa","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":true,"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":0.8359000086784363,"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":0.8359000086784363,"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":0.08070000261068344,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.05119999870657921,"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/network-extraction","display_name":"network extraction","score":0.8090000152587891},{"id":"https://openalex.org/keywords/electrical-circuit-diagrams","display_name":"electrical circuit diagrams","score":0.7789999842643738},{"id":"https://openalex.org/keywords/gpt-4o","display_name":"GPT-4o","score":0.9369999766349792},{"id":"https://openalex.org/keywords/multimodal-language-models","display_name":"multimodal language models","score":0.9559999704360962},{"id":"https://openalex.org/keywords/netlist-generation","display_name":"netlist generation","score":0.8949999809265137},{"id":"https://openalex.org/keywords/component-identification","display_name":"component identification","score":0.6669999957084656},{"id":"https://openalex.org/keywords/retrieval-augmented-generation","display_name":"retrieval-augmented generation","score":0.9449999928474426},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.34299999475479126},{"id":"https://openalex.org/keywords/synthetic-image-dataset","display_name":"synthetic image dataset","score":0.4359999895095825}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8094000220298767},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6589999794960022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6514000296592712},{"id":"https://openalex.org/C177650935","wikidata":"https://www.wikidata.org/wiki/Q1760303","display_name":"Netlist","level":2,"score":0.6238999962806702},{"id":"https://openalex.org/C192328126","wikidata":"https://www.wikidata.org/wiki/Q4514647","display_name":"Schematic","level":2,"score":0.59579998254776},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5171999931335449},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5131999850273132},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.484499990940094},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43549999594688416},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41100001335144043},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.37220001220703125},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.37209999561309814},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.34209999442100525},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3343999981880188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.30809998512268066},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2745000123977661}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:DiVA.org:umu-245829","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-245829","pdf_url":"https://umu.diva-portal.org/smash/get/diva2:2008968/FULLTEXT01","source":{"id":"https://openalex.org/S4306400361","display_name":"DiVA at Ume\u00e5 University (Ume\u00e5 University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I90267481","host_organization_name":"Ume\u00e5 University","host_organization_lineage":["https://openalex.org/I90267481"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bachelorThesis"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:umu-245829","doi":null,"is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-245829","pdf_url":"https://umu.diva-portal.org/smash/get/diva2:2008968/FULLTEXT01","source":{"id":"https://openalex.org/S4306400361","display_name":"DiVA at Ume\u00e5 University (Ume\u00e5 University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I90267481","host_organization_name":"Ume\u00e5 University","host_organization_lineage":["https://openalex.org/I90267481"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/bachelorThesis"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5378999710083008,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7112842953.pdf","grobid_xml":"https://content.openalex.org/works/W7112842953.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1483870316","https://openalex.org/W2626778328","https://openalex.org/W2899663614","https://openalex.org/W3005742798","https://openalex.org/W3030163527","https://openalex.org/W3037932933","https://openalex.org/W4327810158","https://openalex.org/W4389984066","https://openalex.org/W4402352920","https://openalex.org/W4402854593","https://openalex.org/W4411403346","https://openalex.org/W4413278570","https://openalex.org/W6941243218"],"related_works":["https://openalex.org/W7220398088","https://openalex.org/W7128160246","https://openalex.org/W4417084351","https://openalex.org/W4406273429","https://openalex.org/W4406872446","https://openalex.org/W7155608791","https://openalex.org/W4408351862","https://openalex.org/W7126281972","https://openalex.org/W4417183426","https://openalex.org/W4409917704"],"abstract_inverted_index":{"Extracting":[0],"structural":[1],"information":[2,46],"from":[3,100],"images":[4,29,73],"is":[5],"a":[6,138,144],"task":[7,201],"traditionally":[8],"handled":[9],"using":[10,121,238],"object":[11,123],"detection":[12,124],"and":[13,30,94,97,112,125,143,176,251],"rule-based":[14],"methods.":[15],"This":[16],"thesis":[17],"explores":[18],"whether":[19],"general-purpose":[20,209],"multimodal":[21,210],"language":[22],"models,":[23],"specifically":[24],"GPT-4o,":[25],"can":[26],"interpret":[27],"technical":[28],"generate":[31,98],"structured":[32,216],"outputs":[33],"without":[34],"task-specific":[35,252],"fine-tuning.":[36,253],"The":[37,158,179,205],"potential":[38,214],"benefit":[39],"of":[40,53],"this":[41,75],"approach":[42],"lies":[43],"in":[44,74,155,182,223,241],"streamlining":[45],"retrieval":[47],"for":[48,61,66,107,202,215],"organizations":[49],"handling":[50,224],"large":[51],"volumes":[52],"visually":[54],"complex":[55,225],"data,":[56],"potentially":[57],"reducing":[58],"the":[59,134,156,162,198,239],"need":[60],"extensive":[62],"datasets":[63,104],"typically":[64],"required":[65],"training":[67],"traditional":[68,122],"computer":[69],"vision":[70],"systems.":[71],"Technical":[72],"study":[76],"are":[77],"represented":[78],"by":[79,191],"electrical":[80],"circuit":[81,101],"diagrams.":[82],"GPT-4o":[83,136],"was":[84,119,197],"evaluated":[85],"on":[86],"its":[87],"ability":[88],"to":[89,188],"identify":[90],"components,":[91],"produce":[92],"consistent":[93,177],"accurate":[95,175],"responses,":[96],"netlists":[99],"images.":[102],"Two":[103],"were":[105,132,150],"used":[106],"evaluation:":[108],"one":[109,113],"synthetically":[110],"generated,":[111],"manually":[114],"created.":[115],"Ground":[116],"truth":[117],"data":[118],"generated":[120],"image":[126],"processing":[127],"techniques.":[128],"Three":[129],"model":[130],"configurations":[131],"tested:":[133],"original":[135],"model,":[137],"retrieval-augmented":[139],"generation":[140,196],"(RAG)":[141],"version,":[142],"labeled":[145,159],"version":[146],"where":[147],"component":[148],"symbols":[149],"annotated":[151],"with":[152],"textual":[153,171],"labels":[154],"image.":[157],"configuration":[160],"achieved":[161],"highest":[163],"performance":[164],"across":[165],"all":[166,203],"tasks,":[167],"suggesting":[168],"that":[169,208,235],"embedded":[170],"cues":[172],"strongly":[173],"support":[174],"predictions.":[178],"RAG":[180],"setup,":[181],"contrast,":[183],"often":[184],"underperformed,":[185],"possibly":[186],"due":[187],"confusion":[189],"introduced":[190],"loosely":[192],"relevant":[193],"context.":[194],"Netlist":[195],"most":[199],"challenging":[200],"configurations.":[204],"results":[206],"show":[207],"models":[211,240],"have":[212],"some":[213],"visual":[217],"understanding,":[218],"but":[219],"also":[220],"clear":[221],"limitations":[222,230],"domain-specific":[226],"tasks.":[227],"Overcoming":[228],"these":[229],"will":[231],"likely":[232],"require":[233],"methods":[234],"go":[236],"beyond":[237],"their":[242],"current":[243],"form,":[244],"such":[245],"as":[246],"hybrid":[247],"approaches,":[248],"memory-based":[249],"reasoning,":[250]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-12-10T00:00:00"}