{"id":"https://openalex.org/W4409761300","doi":"https://doi.org/10.1109/mci.2025.3540742","title":"Transformer-Assisted Genetic Programming for Symbolic Regression [Research Frontier]","display_name":"Transformer-Assisted Genetic Programming for Symbolic Regression [Research Frontier]","publication_year":2025,"publication_date":"2025-04-24","ids":{"openalex":"https://openalex.org/W4409761300","doi":"https://doi.org/10.1109/mci.2025.3540742"},"language":"en","primary_location":{"id":"doi:10.1109/mci.2025.3540742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2025.3540742","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computational Intelligence Magazine","raw_type":"journal-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/A5101172866","display_name":"Xiaoxu Han","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoxu Han","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-7991-5881","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081658553","display_name":"Jinghui Zhong","orcid":"https://orcid.org/0000-0003-0113-3430"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinghui Zhong","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0113-3430","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100997950","display_name":"Zhitong Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhitong Ma","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042317994","display_name":"Xin Mu","orcid":"https://orcid.org/0000-0002-2747-5677"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Mu","raw_affiliation_strings":["Pengcheng Laboratory, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2747-5677","affiliations":[{"raw_affiliation_string":"Pengcheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5092528070","display_name":"Nikola Gligorovski","orcid":"https://orcid.org/0009-0005-6369-354X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nikola Gligorovski","raw_affiliation_strings":["South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101172866"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":2.1733,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88079912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"20","issue":"2","first_page":"58","last_page":"79"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9998000264167786,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9998000264167786,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9812999963760376,"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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.9509999752044678,"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/symbolic-regression","display_name":"Symbolic regression","score":0.9107998609542847},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.8235539197921753},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6702068448066711},{"id":"https://openalex.org/keywords/frontier","display_name":"Frontier","score":0.6328260898590088},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5169917345046997},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.44643744826316833},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4265042543411255},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.420635849237442},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4103228747844696},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1973084807395935},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1556595265865326},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1171402633190155}],"concepts":[{"id":"https://openalex.org/C2776400721","wikidata":"https://www.wikidata.org/wiki/Q18171762","display_name":"Symbolic regression","level":3,"score":0.9107998609542847},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.8235539197921753},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6702068448066711},{"id":"https://openalex.org/C2778571376","wikidata":"https://www.wikidata.org/wiki/Q1355821","display_name":"Frontier","level":2,"score":0.6328260898590088},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5169917345046997},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.44643744826316833},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4265042543411255},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.420635849237442},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4103228747844696},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1973084807395935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1556595265865326},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1171402633190155},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mci.2025.3540742","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mci.2025.3540742","pdf_url":null,"source":{"id":"https://openalex.org/S104797584","display_name":"IEEE Computational Intelligence Magazine","issn_l":"1556-603X","issn":["1556-603X","1556-6048"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computational Intelligence Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1687323865","display_name":null,"funder_award_id":"62106114","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G267668841","display_name":null,"funder_award_id":"62476096","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4809794565","display_name":null,"funder_award_id":"2023A1515012291","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W102043130","https://openalex.org/W1165902945","https://openalex.org/W1795093649","https://openalex.org/W1980316648","https://openalex.org/W1992283663","https://openalex.org/W1998329127","https://openalex.org/W2006799226","https://openalex.org/W2019625726","https://openalex.org/W2040492000","https://openalex.org/W2049736842","https://openalex.org/W2051434435","https://openalex.org/W2061011797","https://openalex.org/W2076402663","https://openalex.org/W2150295936","https://openalex.org/W2216139323","https://openalex.org/W2346480002","https://openalex.org/W2516977959","https://openalex.org/W2804610053","https://openalex.org/W2891680306","https://openalex.org/W3036412476","https://openalex.org/W3082465854","https://openalex.org/W3160536906","https://openalex.org/W3187435263","https://openalex.org/W4226083102","https://openalex.org/W4283722660","https://openalex.org/W4308177782","https://openalex.org/W4377031057","https://openalex.org/W4385245566","https://openalex.org/W4385834605","https://openalex.org/W4386469307","https://openalex.org/W4388139328","https://openalex.org/W4391770260","https://openalex.org/W4392567326","https://openalex.org/W4393171197","https://openalex.org/W4395093945","https://openalex.org/W4396564048","https://openalex.org/W4396771603","https://openalex.org/W4401416311","https://openalex.org/W4408012455","https://openalex.org/W6683204974","https://openalex.org/W6755903938","https://openalex.org/W6769730313","https://openalex.org/W6773942789","https://openalex.org/W6780346505","https://openalex.org/W6796097400","https://openalex.org/W6797795804","https://openalex.org/W6798732922","https://openalex.org/W6803054178","https://openalex.org/W6810210838","https://openalex.org/W6839132330","https://openalex.org/W6849594578","https://openalex.org/W6859626131","https://openalex.org/W6860327375","https://openalex.org/W6861098061"],"related_works":["https://openalex.org/W2968285896","https://openalex.org/W2381504162","https://openalex.org/W1567571923","https://openalex.org/W2472646430","https://openalex.org/W2610450612","https://openalex.org/W2549153708","https://openalex.org/W1964607451","https://openalex.org/W2897801744","https://openalex.org/W2147355282","https://openalex.org/W2394133867"],"abstract_inverted_index":{"Symbolic":[0],"Regression":[1],"(SR)":[2],"is":[3,147],"a":[4,40,139,148,153],"powerful":[5],"technique":[6,33],"for":[7,34,94,106],"uncovering":[8],"hidden":[9],"mathematical":[10],"expressions":[11],"from":[12,39,58],"observed":[13],"data":[14],"and":[15,22,62,163,182],"has":[16,28],"broad":[17],"applications":[18],"in":[19,115,194],"scientific":[20],"discovery":[21,48],"automatic":[23],"programming.":[24],"Genetic":[25],"Programming":[26],"(GP)":[27],"traditionally":[29],"been":[30],"the":[31,36,47,67,101,122,129,170,175,183,201,204],"dominant":[32],"solving":[35],"SR,":[37],"benefiting":[38],"robust":[41],"global":[42],"search":[43,60],"capability":[44],"that":[45,151,186],"enables":[46],"of":[49,103,126,132,196,203],"solutions":[50],"with":[51,128],"high":[52],"fitting":[53],"accuracy.":[54,116],"Whereas,":[55],"GP":[56,113,127,143],"suffers":[57],"low":[59],"efficiency":[61],"may":[63],"not":[64,189],"fully":[65],"exploit":[66],"accumulated":[68],"knowledge":[69],"to":[70,112,120,157],"accelerate":[71],"convergence.":[72],"Conversely,":[73],"deep":[74],"learning-based":[75],"methods,":[76],"particularly":[77],"those":[78],"employing":[79],"Transformer":[80,134,155],"backbones,":[81],"are":[82,166,180],"trained":[83],"offline":[84],"on":[85,169],"large-scale":[86],"datasets.":[87],"These":[88],"methods":[89,114,193],"exhibit":[90],"strong":[91],"generalization":[92,130],"capabilities":[93,125],"unseen":[95],"tasks":[96,108],"without":[97],"additional":[98],"training.":[99],"However,":[100],"lack":[102],"refinement":[104],"mechanisms":[105],"specific":[107,123],"renders":[109],"them":[110],"inferior":[111],"This":[117],"study":[118],"aims":[119],"combine":[121],"problem-solving":[124],"strengths":[131],"pretrained":[133,140,154],"models.":[135],"Specifically,":[136],"we":[137],"propose":[138],"model":[141,156],"guided":[142],"(PGGP)":[144],"method,":[145],"which":[146],"GP-based":[149],"method":[150,188],"incorporates":[152],"enhance":[158],"SR":[159],"problem-solving.":[160],"New":[161],"initialization":[162],"mutation":[164],"operators":[165],"proposed":[167],"based":[168],"well-structured":[171],"equation":[172],"obtained":[173],"using":[174],"pre-trained":[176],"model.":[177],"Extensive":[178],"experiments":[179],"conducted,":[181],"results":[184],"show":[185],"our":[187],"only":[190],"surpasses":[191],"comparative":[192],"terms":[195],"accuracy":[197],"but":[198],"also":[199],"reduces":[200],"complexity":[202],"generated":[205],"solutions,":[206],"potentially":[207],"enhancing":[208],"interpretability.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
