{"id":"https://openalex.org/W7163534920","doi":"https://doi.org/10.23919/date69613.2026.11539144","title":"Lithography Hotspot Detection for Complex Non-Manhattan Layouts via Graph Neural Network","display_name":"Lithography Hotspot Detection for Complex Non-Manhattan Layouts via Graph Neural Network","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7163534920","doi":"https://doi.org/10.23919/date69613.2026.11539144"},"language":null,"primary_location":{"id":"doi:10.23919/date69613.2026.11539144","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date69613.2026.11539144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 Design, Automation &amp;amp; Test in Europe Conference (DATE)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137847230","display_name":"Bohao Li","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":"Bohao Li","raw_affiliation_strings":["Zhejiang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137900163","display_name":"Ranran Liu","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":"Ranran Liu","raw_affiliation_strings":["Zhejiang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100637929","display_name":"Yumeng Liu","orcid":"https://orcid.org/0000-0003-2198-0653"},"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":"Yumeng Liu","raw_affiliation_strings":["Zhejiang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102595121","display_name":"Jiang Cong","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Jiang","raw_affiliation_strings":["Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013244916","display_name":"K L Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Liu","raw_affiliation_strings":["Huazhong University of Science and Technology,Wuhan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology,Wuhan,China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137900278","display_name":"Bei Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bei Yu","raw_affiliation_strings":["The Chinese University of Hong Kong,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong,China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137811699","display_name":"Kun Ren","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":"Kun Ren","raw_affiliation_strings":["Zhejiang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137852239","display_name":"Qi Sun","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":"Qi Sun","raw_affiliation_strings":["Zhejiang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5137890046","display_name":"Cheng Zhuo","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":"Cheng Zhuo","raw_affiliation_strings":["Zhejiang University,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11338","display_name":"Advancements in Photolithography Techniques","score":0.4284999966621399,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11338","display_name":"Advancements in Photolithography Techniques","score":0.4284999966621399,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12224","display_name":"Nanofabrication and Lithography Techniques","score":0.06360000371932983,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.05339999869465828,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5853000283241272},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41760000586509705},{"id":"https://openalex.org/keywords/lithography","display_name":"Lithography","score":0.41190001368522644},{"id":"https://openalex.org/keywords/hotspot","display_name":"Hotspot (geology)","score":0.350600004196167},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3504999876022339}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6140999794006348},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5853000283241272},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4934000074863434},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41760000586509705},{"id":"https://openalex.org/C204223013","wikidata":"https://www.wikidata.org/wiki/Q133036","display_name":"Lithography","level":2,"score":0.41190001368522644},{"id":"https://openalex.org/C146481406","wikidata":"https://www.wikidata.org/wiki/Q105131","display_name":"Hotspot (geology)","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3212999999523163},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.29789999127388},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.29249998927116394},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2702000141143799}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/date69613.2026.11539144","is_oa":false,"landing_page_url":"https://doi.org/10.23919/date69613.2026.11539144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 Design, Automation &amp;amp; Test in Europe Conference (DATE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6072609424591064,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2057596653","https://openalex.org/W2804151869","https://openalex.org/W2998417722","https://openalex.org/W3048563620","https://openalex.org/W3083181217","https://openalex.org/W3111269108","https://openalex.org/W3199630607","https://openalex.org/W4200227931","https://openalex.org/W4280510627","https://openalex.org/W4379115969","https://openalex.org/W4402830630","https://openalex.org/W4404102066","https://openalex.org/W4407693161","https://openalex.org/W4408024913","https://openalex.org/W4414198273","https://openalex.org/W4416429773"],"related_works":[],"abstract_inverted_index":{"Convolutional":[0],"neural":[1,29],"networks":[2,30],"(CNNs)":[3],"have":[4,32],"been":[5],"widely":[6],"applied":[7],"in":[8,182,196],"lithography":[9],"hotspot":[10,156],"detection":[11],"due":[12],"to":[13,46,65,108,141,153],"their":[14],"strong":[15,44],"feature":[16],"extraction":[17],"capability;":[18],"however,":[19],"low":[20],"computational":[21],"efficiency":[22],"remains":[23],"a":[24,35,75,104,170,179],"critical":[25,83],"bottleneck.":[26],"Recently,":[27],"graph":[28,77,121],"(GNNs)":[31],"emerged":[33],"as":[34],"promising":[36],"alternative,":[37],"offering":[38],"both":[39,110],"high":[40],"inference":[41],"speed":[42],"and":[43,63,112,157,178],"scalability":[45],"variable-sized":[47],"inputs.":[48],"Nevertheless,":[49],"existing":[50],"approaches":[51],"model":[52],"layouts":[53,88],"by":[54,89,99],"decomposing":[55],"polygons":[56],"into":[57,131],"rectangles,":[58],"which":[59],"introduces":[60],"redundant":[61],"boundaries":[62],"struggles":[64],"handle":[66],"complex":[67],"non-Manhattan":[68,87,163,193],"layouts.":[69],"In":[70],"this":[71,197],"paper,":[72],"we":[73,102,135],"propose":[74],"novel":[76],"representation":[78],"that":[79,166],"accurately":[80],"extracts":[81],"the":[82,95,120,123,143,151,187],"geometric":[84],"features":[85],"of":[86,126],"modeling":[90],"polygon":[91],"contours.":[92],"To":[93],"capture":[94],"long-range":[96],"interactions":[97],"induced":[98],"optical":[100],"effects,":[101],"introduce":[103],"hierarchical":[105],"message-passing":[106],"mechanism":[107],"encode":[109],"local":[111],"global":[113],"layout":[114,194],"structures":[115],"efficiently.":[116],"Furthermore,":[117],"building":[118],"on":[119,161],"representation,":[122],"clip-level":[124],"labels":[125],"non-hotspots":[127],"can":[128],"be":[129],"transformed":[130],"edge-level":[132],"supervision.":[133],"Accordingly,":[134],"incorporate":[136],"multiple":[137],"instance":[138],"learning":[139],"(MIL)":[140],"leverage":[142],"fine-grained":[144],"supervision":[145],"from":[146],"non-hotspot":[147,158],"clips,":[148],"thereby":[149],"enhancing":[150],"ability":[152],"distinguish":[154],"between":[155],"clips.":[159],"Experiments":[160],"industrial":[162,192],"datasets":[164],"demonstrate":[165],"our":[167],"method":[168],"yields":[169],"3.6%":[171],"higher":[172],"recall,":[173],"10.8%":[174],"fewer":[175],"false":[176],"alarms,":[177],"1.7%":[180],"increase":[181],"F1":[183],"score":[184],"compared":[185],"with":[186],"state-of-the-art":[188],"(SOTA)":[189],"methods.":[190],"The":[191],"used":[195],"work":[198],"is":[199],"available":[200],"at":[201],"https://github.com/yb-hitsz/DATE2026-GNN4LSD.":[202]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-06-05T00:00:00"}
