{"id":"https://openalex.org/W4408395304","doi":"https://doi.org/10.1145/3698364.3709121","title":"Invited: Artificial Netlist Generation for Enhanced Circuit Data Augmentation","display_name":"Invited: Artificial Netlist Generation for Enhanced Circuit Data Augmentation","publication_year":2025,"publication_date":"2025-03-13","ids":{"openalex":"https://openalex.org/W4408395304","doi":"https://doi.org/10.1145/3698364.3709121"},"language":"en","primary_location":{"id":"doi:10.1145/3698364.3709121","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698364.3709121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Symposium on Physical Design","raw_type":"proceedings-article"},"type":"article","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/A5044543389","display_name":"Seokhyeong Kang","orcid":"https://orcid.org/0000-0003-3015-1806"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seokhyeong Kang","raw_affiliation_strings":["POSTECH, Pohang, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"POSTECH, Pohang, Republic of Korea","institution_ids":["https://openalex.org/I123900574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5044543389"],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02145528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"163","last_page":"163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13293","display_name":"Engineering and Test Systems","score":0.9562000036239624,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/netlist","display_name":"Netlist","score":0.9715678691864014},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6603822112083435},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.21161386370658875}],"concepts":[{"id":"https://openalex.org/C177650935","wikidata":"https://www.wikidata.org/wiki/Q1760303","display_name":"Netlist","level":2,"score":0.9715678691864014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6603822112083435},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.21161386370658875}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3698364.3709121","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698364.3709121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Symposium on Physical Design","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W4312872986","https://openalex.org/W4389162997","https://openalex.org/W4409285501"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2170314243","https://openalex.org/W2119179026","https://openalex.org/W2794947590","https://openalex.org/W2114971758","https://openalex.org/W2109932036","https://openalex.org/W2093081283","https://openalex.org/W4313118781"],"abstract_inverted_index":{"Optimizing":[0],"power,":[1],"performance,":[2],"and":[3,14,27,48,138,171],"area":[4],"(PPA)":[5],"at":[6],"advanced":[7],"nodes":[8],"has":[9,55,95],"become":[10],"an":[11],"increasingly":[12],"challenging":[13],"complex":[15],"task.":[16],"To":[17],"address":[18,63,135],"these":[19],"challenges,":[20],"approaches":[21],"such":[22],"as":[23,33],"machine":[24],"learning":[25],"(ML)":[26],"design-technology":[28],"co-optimization":[29],"(DTCO)":[30],"have":[31],"emerged":[32],"promising":[34],"solutions.":[35],"However,":[36],"their":[37],"effectiveness":[38],"is":[39],"limited":[40],"by":[41],"the":[42,64,75,89,100,173],"lack":[43],"of":[44,66,77,102,159],"diverse":[45],"training":[46],"data":[47,54,73,94,105,136],"prolonged":[49],"turnaround":[50],"times":[51],"(TAT).":[52],"Artificial":[53,109],"been":[56],"widely":[57],"used":[58],"in":[59,88,112,141],"various":[60],"fields":[61],"to":[62,84,125,154],"limitations":[65],"real-world":[67,103,169],"data.":[68],"By":[69,121],"augmenting":[70],"datasets,":[71],"artificial":[72,93,127,152],"improve":[74],"robustness":[76],"ML":[78,164],"models":[79],"against":[80],"input":[81],"perturbations,":[82],"leading":[83],"improved":[85],"performance.":[86],"Similarly,":[87],"physical":[90,142],"design":[91],"flow,":[92],"great":[96],"potential":[97],"for":[98,118,167],"overcoming":[99],"scarcity":[101,137],"circuit":[104,128,160],"[1],":[106],"[2],":[107],"[3].":[108],"circuits":[110,153,170],"proposed":[111],"previous":[113],"studies":[114],"are":[115],"typically":[116],"designed":[117],"specific":[119],"applications.":[120],"developing":[122],"a":[123,156],"method":[124],"generate":[126],"which":[129],"resemble":[130],"real":[131],"circuits,":[132],"we":[133,147],"can":[134,162],"TAT":[139],"challenges":[140],"design.":[143],"In":[144],"this":[145],"talk,":[146],"will":[148],"discuss":[149],"how":[150],"leveraging":[151],"explore":[155],"wide":[157],"range":[158],"characteristics":[161],"enhance":[163],"model":[165],"performance":[166],"unseen":[168],"accelerate":[172],"PPA":[174],"exploration":[175],"flow.":[176]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}