{"id":"https://openalex.org/W7134971079","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420620","title":"CausalTuner: Will Causality Help High-Dimensional EDA Tool Parameter Tuning","display_name":"CausalTuner: Will Causality Help High-Dimensional EDA Tool Parameter Tuning","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7134971079","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420620"},"language":null,"primary_location":{"id":"doi:10.1109/asp-dac66049.2026.11420620","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420620","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)","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/A5066842835","display_name":"Ziyang Yu","orcid":"https://orcid.org/0000-0002-6656-3741"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Ziyang Yu","raw_affiliation_strings":["CUHK"],"affiliations":[{"raw_affiliation_string":"CUHK","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128719337","display_name":"Peng Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Peng Xu","raw_affiliation_strings":["CUHK"],"affiliations":[{"raw_affiliation_string":"CUHK","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128737430","display_name":"Su Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Su Zheng","raw_affiliation_strings":["CUHK"],"affiliations":[{"raw_affiliation_string":"CUHK","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128716995","display_name":"Siyuan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Siyuan Xu","raw_affiliation_strings":["Huawei Noah&#x2019;s Ark Lab"],"affiliations":[{"raw_affiliation_string":"Huawei Noah&#x2019;s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101413344","display_name":"Hao Geng","orcid":"https://orcid.org/0000-0002-0943-7714"},"institutions":[{"id":"https://openalex.org/I30809798","display_name":"ShanghaiTech University","ror":"https://ror.org/030bhh786","country_code":"CN","type":"education","lineage":["https://openalex.org/I30809798"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Geng","raw_affiliation_strings":["ShanghaiTech University"],"affiliations":[{"raw_affiliation_string":"ShanghaiTech University","institution_ids":["https://openalex.org/I30809798"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128738653","display_name":"Bei Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Bei Yu","raw_affiliation_strings":["CUHK"],"affiliations":[{"raw_affiliation_string":"CUHK","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053378706","display_name":"Martin D. F. Wong","orcid":"https://orcid.org/0000-0001-8274-9688"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Martin Wong","raw_affiliation_strings":["HKBU"],"affiliations":[{"raw_affiliation_string":"HKBU","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5066842835"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.9198857,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"370","last_page":"376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.3935999870300293,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.3935999870300293,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.11649999767541885,"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/T10142","display_name":"Formal Methods in Verification","score":0.040800001472234726,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/causality","display_name":"Causality (physics)","score":0.4092999994754791},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3192000091075897},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.296999990940094},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.26260000467300415},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.25130000710487366}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5648999810218811},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.4092999994754791},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3192000091075897},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26899999380111694},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26260000467300415},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2378000020980835},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2378000020980835}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asp-dac66049.2026.11420620","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420620","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 31st Asia and South Pacific Design Automation Conference (ASP-DAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2143891888","https://openalex.org/W2345855315","https://openalex.org/W2944892277","https://openalex.org/W3013899498","https://openalex.org/W3042858012","https://openalex.org/W3206022579","https://openalex.org/W4226441354","https://openalex.org/W4378218479","https://openalex.org/W4409306177","https://openalex.org/W7133234950"],"related_works":[],"abstract_inverted_index":{"Electronic":[0],"Design":[1],"Automation":[2],"(EDA)":[3],"tools":[4],"are":[5],"central":[6],"to":[7,94],"Very":[8],"Large":[9],"Scale":[10],"Integration":[11],"(VLSI)":[12],"design,":[13],"where":[14,64],"numerous":[15],"parameters":[16,53],"govern":[17],"the":[18,31,44,58],"Quality-of-Result":[19],"(QoR)":[20],"metrics,":[21],"including":[22],"performance,":[23],"power,":[24],"and":[25,42,99,109,131],"area.":[26],"The":[27,113],"high":[28],"dimensionality":[29],"of":[30,46],"parameter":[32,85,97],"space,":[33],"coupled":[34],"with":[35],"complex":[36],"interactions,":[37],"makes":[38],"manual":[39],"tuning":[40],"inefficient":[41],"hinders":[43],"scalability":[45],"automated":[47],"methods.":[48],"Existing":[49],"methods":[50,126],"typically":[51],"treat":[52],"as":[54],"flat":[55],"vectors,":[56],"neglecting":[57],"EDA":[59],"flow\u2019s":[60],"hierarchical":[61],"causal":[62,91,114],"structure,":[63],"early-stage":[65],"decisions":[66],"constrain":[67],"later":[68],"downstream":[69],"stages.":[70],"To":[71],"address":[72],"this,":[73],"we":[74],"propose":[75],"CausalTuner,":[76],"a":[77,89],"causality-aware":[78],"design":[79],"space":[80],"exploration":[81,115],"framework":[82],"for":[83,107],"efficient":[84],"tuning.":[86],"It":[87],"employs":[88],"hybrid":[90],"attention":[92],"mechanism":[93],"capture":[95],"stage-wise":[96],"interactions":[98],"embeds":[100],"them":[101],"into":[102],"deep":[103],"kernel":[104],"Gaussian":[105],"processes":[106],"accurate":[108],"generalizable":[110],"surrogate":[111],"modeling.":[112],"strategies":[116],"enhance":[117],"sampling":[118],"efficiency.":[119,132],"Experiments":[120],"show":[121],"that":[122],"CausalTuner":[123],"outperforms":[124],"state-of-the-art":[125],"in":[127],"both":[128],"final":[129],"QoR":[130]},"counts_by_year":[],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2026-03-12T00:00:00"}
