{"id":"https://openalex.org/W4408163925","doi":"https://doi.org/10.1145/3658617.3697594","title":"DeepSeq2: Enhanced Sequential Circuit Learning with Disentangled Representations","display_name":"DeepSeq2: Enhanced Sequential Circuit Learning with Disentangled Representations","publication_year":2025,"publication_date":"2025-01-20","ids":{"openalex":"https://openalex.org/W4408163925","doi":"https://doi.org/10.1145/3658617.3697594"},"language":"en","primary_location":{"id":"doi:10.1145/3658617.3697594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658617.3697594","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3658617.3697594","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sadaf Khan","orcid":"https://orcid.org/0000-0003-1696-3429"},"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":"Sadaf Khan","raw_affiliation_strings":["The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-1696-3429","affiliations":[{"raw_affiliation_string":"The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091583458","display_name":"Zhengyuan Shi","orcid":"https://orcid.org/0000-0002-2186-9579"},"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":"Zhengyuan Shi","raw_affiliation_strings":["The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-2186-9579","affiliations":[{"raw_affiliation_string":"The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ziyang Zheng","orcid":"https://orcid.org/0009-0001-6049-0457"},"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":"Ziyang Zheng","raw_affiliation_strings":["The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0009-0001-6049-0457","affiliations":[{"raw_affiliation_string":"The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112109364","display_name":"Min Li","orcid":"https://orcid.org/0000-0002-5486-2947"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Li","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-5486-2947","affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088556682","display_name":"Qiang Xu","orcid":"https://orcid.org/0000-0001-6747-126X"},"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":"Qiang Xu","raw_affiliation_strings":["The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-6747-126X","affiliations":[{"raw_affiliation_string":"The Chinese Univ. of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.2763,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.94695527,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"498","last_page":"504"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9979000091552734,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9979000091552734,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9979000091552734,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9965999722480774,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6428337097167969},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3873675465583801},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3253780007362366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6428337097167969},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3873675465583801},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3253780007362366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3658617.3697594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658617.3697594","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3658617.3697594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658617.3697594","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th Asia and South Pacific Design Automation Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1528837436","https://openalex.org/W2026124051","https://openalex.org/W2143727503","https://openalex.org/W2322411027","https://openalex.org/W2519887557","https://openalex.org/W2624431344","https://openalex.org/W2808707363","https://openalex.org/W2911910392","https://openalex.org/W2912450141","https://openalex.org/W2918342466","https://openalex.org/W2942465004","https://openalex.org/W3092027164","https://openalex.org/W3198659451","https://openalex.org/W4200088851","https://openalex.org/W4221158934","https://openalex.org/W4234212765","https://openalex.org/W4285524154","https://openalex.org/W4293024139","https://openalex.org/W4293261952","https://openalex.org/W4307413815","https://openalex.org/W4312725592","https://openalex.org/W4386764162","https://openalex.org/W4386767094","https://openalex.org/W4389161199","https://openalex.org/W4389166679","https://openalex.org/W4400188660","https://openalex.org/W6778883912","https://openalex.org/W6788695333","https://openalex.org/W6846529617","https://openalex.org/W6847131820","https://openalex.org/W6850093540","https://openalex.org/W6850600502","https://openalex.org/W6856635174"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Circuit":[0],"representation":[1,81,140],"learning":[2,29,60],"is":[3],"increasingly":[4],"pivotal":[5],"in":[6,106,137,145],"Electronic":[7],"Design":[8],"Automation":[9],"(EDA),":[10],"serving":[11],"various":[12],"downstream":[13],"tasks":[14],"with":[15],"enhanced":[16],"model":[17,115],"efficiency":[18],"and":[19,44,74,113,148],"accuracy.":[20],"One":[21],"notable":[22],"work,":[23],"DeepSeq,":[24,107],"has":[25],"pioneered":[26],"sequential":[27,62,75,138],"circuit":[28,88,139],"by":[30,64],"encoding":[31],"temporal":[32],"correlations.":[33],"However,":[34],"it":[35,67],"suffers":[36],"from":[37],"significant":[38],"limitations":[39],"including":[40],"prolonged":[41],"execution":[42,111],"times":[43,112],"architectural":[45],"inefficiencies.":[46],"To":[47],"address":[48],"these":[49],"issues,":[50],"we":[51],"introduce":[52],"DeepSeq2,":[53],"a":[54,78,120,134],"novel":[55],"framework":[56],"that":[57,82,100,124],"enhances":[58],"the":[59,84,102],"of":[61,87],"circuits,":[63],"innovatively":[65],"mapping":[66],"into":[68],"three":[69],"distinct":[70],"embedding":[71],"spaces---structure,":[72],"function,":[73],"behavior---allowing":[76],"for":[77],"more":[79,130],"nuanced":[80],"captures":[83,125],"inherent":[85],"complexities":[86],"dynamics.":[89],"By":[90],"employing":[91],"an":[92],"efficient":[93],"Directed":[94],"Acyclic":[95],"Graph":[96],"Neural":[97],"Network":[98],"(DAG-GNN)":[99],"circumvents":[101],"recursive":[103],"propagation":[104],"used":[105],"DeepSeq2":[108,118,132],"significantly":[109],"reduces":[110],"improves":[114],"scalability.":[116],"Moreover,":[117],"incorporates":[119],"unique":[121],"supervision":[122],"mechanism":[123],"transitioning":[126],"behaviors":[127],"within":[128],"circuits":[129],"effectively.":[131],"sets":[133],"new":[135],"benchmark":[136],"learning,":[141],"outperforming":[142],"prior":[143],"works":[144],"power":[146],"estimation":[147],"reliability":[149],"analysis.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}