{"id":"https://openalex.org/W4411725540","doi":"https://doi.org/10.1109/iscas56072.2025.11043832","title":"Enhancing LLM Performance on Hardware Design Generation Task via Reinforcement Learning","display_name":"Enhancing LLM Performance on Hardware Design Generation Task via Reinforcement Learning","publication_year":2025,"publication_date":"2025-05-25","ids":{"openalex":"https://openalex.org/W4411725540","doi":"https://doi.org/10.1109/iscas56072.2025.11043832"},"language":"en","primary_location":{"id":"doi:10.1109/iscas56072.2025.11043832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas56072.2025.11043832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5100929104","display_name":"Yi\u2010Fang Zhao","orcid":"https://orcid.org/0009-0000-1874-4567"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifang Zhao","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062517894","display_name":"Weimin Fu","orcid":"https://orcid.org/0000-0002-9623-6522"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weimin Fu","raw_affiliation_strings":["Kansas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061493911","display_name":"Shijie Li","orcid":"https://orcid.org/0000-0001-9421-7064"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shijie Li","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024558170","display_name":"Yi Hu","orcid":"https://orcid.org/0000-0001-7115-374X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi-Xiang Hu","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076198928","display_name":"Xiaolong Guo","orcid":"https://orcid.org/0000-0002-1261-6852"},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolong Guo","raw_affiliation_strings":["Kansas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017464942","display_name":"Yier Jin","orcid":"https://orcid.org/0000-0002-8791-0597"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yier Jin","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9506999850273132,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9506999850273132,"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9319000244140625,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T10558","display_name":"Advancements in Semiconductor Devices and Circuit Design","score":0.925599992275238,"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/computer-science","display_name":"Computer science","score":0.7502065300941467},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7283652424812317},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6403679251670837},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.5261659026145935},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.38668543100357056},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.3638181686401367},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3529737591743469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24872341752052307},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17676663398742676},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.17204341292381287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7502065300941467},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7283652424812317},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6403679251670837},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.5261659026145935},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.38668543100357056},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.3638181686401367},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3529737591743469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24872341752052307},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17676663398742676},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.17204341292381287}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas56072.2025.11043832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas56072.2025.11043832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W3028737568","https://openalex.org/W3089396352","https://openalex.org/W3205090792","https://openalex.org/W4226171879","https://openalex.org/W4280592917","https://openalex.org/W4285114951","https://openalex.org/W4312795547","https://openalex.org/W4386185625","https://openalex.org/W4388040405","https://openalex.org/W4389166737","https://openalex.org/W4390041933","https://openalex.org/W4391182436","https://openalex.org/W4392544408","https://openalex.org/W4393145520","https://openalex.org/W4396831993","https://openalex.org/W4402671783","https://openalex.org/W4403023622","https://openalex.org/W4404739285","https://openalex.org/W6739901393","https://openalex.org/W6770320521","https://openalex.org/W6796581206","https://openalex.org/W6798182279","https://openalex.org/W6810738896","https://openalex.org/W6850625674","https://openalex.org/W6852056849","https://openalex.org/W6852418670","https://openalex.org/W6852800892","https://openalex.org/W6852952922","https://openalex.org/W6853837529","https://openalex.org/W6855873652","https://openalex.org/W6857951434","https://openalex.org/W6858189809","https://openalex.org/W6860976335","https://openalex.org/W6861749967"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W2024136090","https://openalex.org/W4391331176","https://openalex.org/W2031695474","https://openalex.org/W2586732548","https://openalex.org/W2964765435"],"abstract_inverted_index":{"Integrated":[0],"circuit":[1],"design":[2,18],"is":[3,20,27,35],"a":[4,77,130,136,143],"highly":[5],"complex":[6],"and":[7,64,90,108,125,135],"time-consuming":[8],"process.":[9,40],"Leveraging":[10],"large":[11],"language":[12],"models":[13],"(LLMs)":[14],"for":[15],"automating":[16],"hardware":[17,53,70,102,112],"generation":[19],"receiving":[21],"increasing":[22],"attention.":[23],"A":[24],"prominent":[25],"challenge":[26],"that":[28,84,117],"the":[29,33,38,57,65,98,106,118],"inherent":[30,68],"structure":[31],"of":[32,100,111],"text":[34],"overlooked":[36],"during":[37],"training":[39],"Existing":[41],"efforts":[42],"focus":[43],"on":[44,133,139,146],"supervised":[45],"fine-tuning":[46],"LLMs":[47],"to":[48],"acquire":[49],"specialized":[50],"knowledge":[51],"in":[52,69],"design,":[54],"without":[55],"considering":[56],"conflict":[58],"between":[59],"LLMs\u2019":[60],"linear":[61],"data":[62],"processing":[63],"structural":[66],"nature":[67],"design.":[71],"In":[72],"this":[73],"work,":[74],"we":[75],"propose":[76],"novel":[78],"LLM-based":[79],"reinforcement":[80],"learning":[81],"(RL)":[82],"framework":[83],"integrates":[85],"Abstract":[86],"Syntax":[87],"Trees":[88],"(ASTs)":[89],"Data":[91],"Flow":[92],"Graphs":[93],"(DFGs).":[94],"Our":[95],"approach":[96],"enhances":[97],"accuracy":[99],"generated":[101],"code":[103],"by":[104],"capturing":[105],"syntactic":[107],"semantic":[109],"structures":[110],"designs.":[113],"Experimental":[114],"results":[115],"show":[116],"SFT-RL":[119],"model":[120],"integrated":[121],"with":[122],"Text,":[123],"AST,":[124],"DFG":[126],"achieves":[127],"notable":[128],"improvements:":[129],"12.57%":[131],"increase":[132,138],"VerilogEval-Human":[134],"5.49%":[137],"VerilogEval-Machine,":[140],"outperforming":[141],"GPT-4;":[142],"14.29%":[144],"improvement":[145],"RTLLM,":[147],"approaching":[148],"GPT-4.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}