{"id":"https://openalex.org/W4409282777","doi":"https://doi.org/10.1145/3676536.3676750","title":"FabGPT: An Efficient Large Multimodal Model for Complex Wafer Defect Knowledge Queries","display_name":"FabGPT: An Efficient Large Multimodal Model for Complex Wafer Defect Knowledge Queries","publication_year":2024,"publication_date":"2024-10-27","ids":{"openalex":"https://openalex.org/W4409282777","doi":"https://doi.org/10.1145/3676536.3676750"},"language":"en","primary_location":{"id":"doi:10.1145/3676536.3676750","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3676536.3676750","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3676750","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3676750","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102712744","display_name":"Yuqi Jiang","orcid":"https://orcid.org/0009-0002-4059-4854"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqi Jiang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-4059-4854","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066777981","display_name":"Xudong Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Lu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-9082-4084","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109507749","display_name":"Qian Jin","orcid":"https://orcid.org/0009-0009-4414-232X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Jin","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0009-4414-232X","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427492","display_name":"Qi Sun","orcid":"https://orcid.org/0000-0001-5153-6698"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Sun","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5153-6698","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110944691","display_name":"Hanming Wu","orcid":"https://orcid.org/0009-0007-7540-5546"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanming Wu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-7540-5546","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054211420","display_name":"Cheng Zhuo","orcid":"https://orcid.org/0000-0002-2610-7522"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Zhuo","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2610-7522","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9062,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.93809602,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9812999963760376,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9746000170707703,"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/computer-science","display_name":"Computer science","score":0.7068176865577698},{"id":"https://openalex.org/keywords/wafer","display_name":"Wafer","score":0.6459580659866333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32549983263015747},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.18703854084014893},{"id":"https://openalex.org/keywords/optoelectronics","display_name":"Optoelectronics","score":0.11327317357063293}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7068176865577698},{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.6459580659866333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32549983263015747},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.18703854084014893},{"id":"https://openalex.org/C49040817","wikidata":"https://www.wikidata.org/wiki/Q193091","display_name":"Optoelectronics","level":1,"score":0.11327317357063293}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3676536.3676750","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3676536.3676750","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3676750","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3676536.3676750","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3676536.3676750","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3676536.3676750","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2781527179","display_name":null,"funder_award_id":"62034007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409282777.pdf","grobid_xml":"https://content.openalex.org/works/W4409282777.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W589744691","https://openalex.org/W1998255627","https://openalex.org/W2110757760","https://openalex.org/W2432481613","https://openalex.org/W2518108298","https://openalex.org/W2616957565","https://openalex.org/W2884561390","https://openalex.org/W2902930830","https://openalex.org/W2920311927","https://openalex.org/W2964245146","https://openalex.org/W2981689412","https://openalex.org/W3039201763","https://openalex.org/W3121523901","https://openalex.org/W3135367836","https://openalex.org/W3189556521","https://openalex.org/W4210430458","https://openalex.org/W4224928693","https://openalex.org/W4229019932","https://openalex.org/W4281724000","https://openalex.org/W4283835269","https://openalex.org/W4310827333","https://openalex.org/W4312289809","https://openalex.org/W4318718936","https://openalex.org/W4322718191","https://openalex.org/W4366850747","https://openalex.org/W4376653731","https://openalex.org/W4385958573","https://openalex.org/W4385965919","https://openalex.org/W4386047758","https://openalex.org/W4386071651","https://openalex.org/W4386071707","https://openalex.org/W4386302907","https://openalex.org/W6742348326","https://openalex.org/W6757817989","https://openalex.org/W6852447913","https://openalex.org/W6852600418","https://openalex.org/W6853163053"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W1998662473","https://openalex.org/W1988252515","https://openalex.org/W2075391483","https://openalex.org/W2742348144","https://openalex.org/W2390279801","https://openalex.org/W2038820605","https://openalex.org/W4391913857"],"abstract_inverted_index":{"Intelligence":[0],"is":[1],"key":[2],"to":[3,77,117],"advancing":[4],"integrated":[5],"circuit":[6],"(IC)":[7],"fabrication.":[8,27],"Recent":[9],"breakthroughs":[10],"in":[11,20,51,55,141],"Large":[12],"Multimodal":[13],"Models":[14],"(LMMs)":[15],"have":[16],"unlocked":[17],"extraditionary":[18],"abilities":[19],"understanding":[21],"images":[22],"and":[23,65,86,99,120,123,145],"text,":[24],"fostering":[25],"intelligent":[26],"Leveraging":[28],"the":[29,88,95,109,125],"power":[30],"of":[31,90],"LMMs,":[32],"we":[33],"introduce":[34],"FabGPT,":[35],"a":[36],"customized":[37],"IC":[38],"fabrication":[39,70],"large":[40],"multimodal":[41,75],"model":[42],"for":[43],"wafer":[44,84,105,142],"defect":[45,53,106,118,143],"knowledge":[46,107,119,122,146],"query.":[47],"FabGPT":[48,72,136],"manifests":[49],"expertise":[50],"conducting":[52],"detection":[54,144],"Scanning":[56],"Electron":[57],"Microscope":[58],"(SEM)":[59],"images,":[60],"performing":[61],"root":[62],"cause":[63],"analysis,":[64],"providing":[66],"expert":[67],"Q&A":[68,114],"on":[69,130],"processes.":[71],"matches":[73],"enhanced":[74],"features":[76],"automatically":[78],"detect":[79],"minute":[80],"defects":[81],"under":[82],"complex":[83],"backgrounds":[85],"reduce":[87],"subjectivity":[89],"manual":[91],"threshold":[92],"settings.":[93],"Besides,":[94],"proposed":[96],"modulation":[97],"module":[98],"interactive":[100],"corpus":[101],"training":[102],"strategy":[103],"embed":[104],"into":[108],"pre-trained":[110],"model,":[111],"effectively":[112],"balancing":[113],"queries":[115],"related":[116],"original":[121],"mitigating":[124],"modality":[126],"bias":[127],"issues.":[128],"Experiments":[129],"in-house":[131],"fab":[132],"data":[133],"show":[134],"that":[135],"achieves":[137],"significant":[138],"performance":[139],"improvement":[140],"querying.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10}],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2025-10-10T00:00:00"}
