{"id":"https://openalex.org/W7134966163","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420511","title":"DUALPlace: Reinforcement Learning based Mixed-size Placement with Multi Modal Cross Attention","display_name":"DUALPlace: Reinforcement Learning based Mixed-size Placement with Multi Modal Cross Attention","publication_year":2026,"publication_date":"2026-01-19","ids":{"openalex":"https://openalex.org/W7134966163","doi":"https://doi.org/10.1109/asp-dac66049.2026.11420511"},"language":null,"primary_location":{"id":"doi:10.1109/asp-dac66049.2026.11420511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420511","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/A5101927125","display_name":"Yanqi Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yue Wu","raw_affiliation_strings":["Hangzhou Dianzi University"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100680695","display_name":"Hu Liu","orcid":"https://orcid.org/0000-0003-2225-7387"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hu Liu","raw_affiliation_strings":["Hangzhou Dianzi University"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128698118","display_name":"Jiayi Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayi Ding","raw_affiliation_strings":["Hangzhou Dianzi University"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128725178","display_name":"Junwei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junwei Li","raw_affiliation_strings":["Hangzhou Dianzi University"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128761350","display_name":"Tieming Han","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tieming Han","raw_affiliation_strings":["Hangzhou Dianzi University"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128787789","display_name":"Xiaoyan Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Yang","raw_affiliation_strings":["Hangzhou Dianzi University"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101927125"],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.91919758,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"945","last_page":"951"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1632000058889389,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.1632000058889389,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.14920000731945038,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.10220000147819519,"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/modal","display_name":"Modal","score":0.474700003862381},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4401000142097473},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3327000141143799},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.3167000114917755},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.31540000438690186},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.3010999858379364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6062999963760376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49549999833106995},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.474700003862381},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4401000142097473},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26030001044273376}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asp-dac66049.2026.11420511","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asp-dac66049.2026.11420511","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1973505932","https://openalex.org/W2003145440","https://openalex.org/W2132693178","https://openalex.org/W2161629461","https://openalex.org/W2884307971","https://openalex.org/W2945592068","https://openalex.org/W3140720939","https://openalex.org/W3151130473","https://openalex.org/W3171752851","https://openalex.org/W4226435553","https://openalex.org/W4292092927","https://openalex.org/W4318580658","https://openalex.org/W4379116093","https://openalex.org/W4392607893","https://openalex.org/W7133190394","https://openalex.org/W7133217793"],"related_works":[],"abstract_inverted_index":{"As":[0],"modern":[1],"circuits":[2],"scale":[3],"up,":[4],"chip":[5],"placement":[6,20,29,54,132],"becomes":[7],"increasingly":[8],"challenging.":[9],"Reinforcement":[10],"learning":[11],"(RL)":[12],"algorithms":[13],"have":[14],"shown":[15],"promise":[16],"in":[17,143,154],"achieving":[18],"high-performance":[19],"outcomes.":[21],"However,":[22],"existing":[23],"RL":[24,48,124],"approaches":[25],"struggled":[26],"with":[27,114,149],"mixed-size":[28,53],"challenges":[30],"primarily":[31],"due":[32],"to":[33,36,93,105,127],"their":[34],"inability":[35],"model":[37],"interdependencies":[38],"between":[39],"heterogeneous":[40],"components":[41],"during":[42],"co-optimization.":[43],"This":[44],"study":[45],"introduced":[46],"an":[47,123],"framework":[49],"specifically":[50],"designed":[51],"for":[52,60,76],"called":[55],"DUALPlace.":[56],"DUALPlace":[57,81,135],"leveraged":[58],"cross-attention":[59,66],"multi-modal":[61],"fusion,":[62],"combining":[63],"a":[64,71,98],"multi-scale":[65],"vision":[67,91],"transformer":[68],"(Cross-ViT)":[69],"and":[70,118,141,145,151,159],"graph":[72,111],"attention":[73],"network":[74],"(GAT)":[75],"different":[77],"modal":[78],"feature":[79,92],"extraction.":[80],"incorporated":[82],"net":[83],"density":[84,163],"maps":[85],"as":[86],"part":[87],"of":[88,101,139],"the":[89,109,128,167],"global":[90],"enhance":[94],"congestion":[95],"analysis,":[96],"providing":[97],"detailed":[99],"view":[100],"layout":[102],"congestion.":[103],"Additionally,":[104],"reduce":[106],"diffusion":[107],"iterations,":[108],"netlist":[110],"was":[112],"partitioned":[113],"fixed":[115],"macro":[116],"vertices":[117],"initially":[119],"placed":[120],"together":[121],"by":[122],"agent.":[125],"Compared":[126],"state-of-the-art":[129],"online":[130],"RL-based":[131],"method":[133],"DeepTH,":[134],"demonstrated":[136],"significant":[137],"enhancements":[138],"79.58%":[140],"48.09%":[142],"iteration":[144],"runtime":[146],"efficiencies,":[147],"along":[148],"5.08%":[150],"10.52%":[152],"improvements":[153],"half-perimeter":[155],"wire":[156,162],"length":[157],"(HPWL)":[158],"rectangular":[160],"uniform":[161],"(RUDY)":[164],"metrics":[165],"on":[166],"ISPD2015":[168],"benchmarks.":[169]},"counts_by_year":[],"updated_date":"2026-03-13T14:20:09.374765","created_date":"2026-03-12T00:00:00"}