{"id":"https://openalex.org/W4403586339","doi":"https://doi.org/10.48550/arxiv.2409.04114","title":"Multi-Programming Language Ensemble for Code Generation in Large Language Model","display_name":"Multi-Programming Language Ensemble for Code Generation in Large Language Model","publication_year":2024,"publication_date":"2024-09-06","ids":{"openalex":"https://openalex.org/W4403586339","doi":"https://doi.org/10.48550/arxiv.2409.04114"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2409.04114","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.04114","pdf_url":"https://arxiv.org/pdf/2409.04114","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2409.04114","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107077523","display_name":"Tengfei Xue","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xue, Tengfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Li, Xuefeng","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xuefeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014635883","display_name":"Tahir Azim","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Azim, Tahir","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107077524","display_name":"Roman Smirnov","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Smirnov, Roman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102204862","display_name":"Jianhui Yu","orcid":"https://orcid.org/0009-0004-9311-2593","observed_orcids":["https://orcid.org/0009-0004-9311-2593"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Jianhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067195415","display_name":"Arash Sadrieh","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sadrieh, Arash","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5107077526","display_name":"Babak Pahlavan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pahlavan, Babak","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10260","display_name":"Software Engineering Research","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10028","display_name":"Topic Modeling","score":0.002199999988079071,"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/T10533","display_name":"Teaching and Learning Programming","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/large-language-models","display_name":"large language models","score":0.746999979019165},{"id":"https://openalex.org/keywords/code-generation","display_name":"code generation","score":0.8259999752044678},{"id":"https://openalex.org/keywords/monte-carlo-tree-search","display_name":"Monte Carlo tree search","score":0.996999979019165},{"id":"https://openalex.org/keywords/programming-languages","display_name":"programming languages","score":0.3840000033378601}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7201038599014282},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.658359169960022},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5490104556083679},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.437109112739563},{"id":"https://openalex.org/C570499","wikidata":"https://www.wikidata.org/wiki/Q1289116","display_name":"First-generation programming language","level":3,"score":0.42508938908576965},{"id":"https://openalex.org/C34165917","wikidata":"https://www.wikidata.org/wiki/Q188267","display_name":"Programming paradigm","level":2,"score":0.32985514402389526},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.30000126361846924},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2409.04114","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.04114","pdf_url":"https://arxiv.org/pdf/2409.04114","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2409.04114","doi":"https://doi.org/10.48550/arxiv.2409.04114","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2409.04114","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2409.04114","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.04114","pdf_url":"https://arxiv.org/pdf/2409.04114","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403586339.pdf","grobid_xml":"https://content.openalex.org/works/W4403586339.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W3177813494","https://openalex.org/W3195140297","https://openalex.org/W4327810158","https://openalex.org/W4366204357","https://openalex.org/W4386185625","https://openalex.org/W4390092490","https://openalex.org/W4390833862","https://openalex.org/W4399696137","https://openalex.org/W4401306886","https://openalex.org/W4402345581","https://openalex.org/W4402671883","https://openalex.org/W4409362450"],"related_works":["https://openalex.org/W4300989059","https://openalex.org/W7083316225","https://openalex.org/W4416098280","https://openalex.org/W4366204357","https://openalex.org/W7117124031","https://openalex.org/W7131786218","https://openalex.org/W7203993382","https://openalex.org/W4417132388","https://openalex.org/W7165376407","https://openalex.org/W4414816475"],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2],"(LLMs)":[3],"have":[4,39],"significantly":[5],"improved":[6],"code":[7,12,22,76,90,154,198],"generation,":[8],"particularly":[9],"in":[10,23],"one-pass":[11],"generation.":[13],"However,":[14],"most":[15],"existing":[16,173],"approaches":[17],"focus":[18],"solely":[19],"on":[20,172,185],"generating":[21],"a":[24,49,70,179],"single":[25],"programming":[26,80,120],"language,":[27],"overlooking":[28],"the":[29,33,115,123,144,186],"potential":[30],"of":[31,36,42,118,182],"leveraging":[32,57],"multi-language":[34,59,111],"capabilities":[35],"LLMs.":[37],"LLMs":[38],"varying":[40],"patterns":[41],"errors":[43,107],"across":[44,78,193],"different":[45,119],"languages,":[46,121],"suggesting":[47],"that":[48,74,161],"more":[50,127],"robust":[51,130],"approach":[52,133],"could":[53],"be":[54,135,200],"developed":[55],"by":[56,168],"these":[58],"outputs.":[60],"In":[61],"this":[62],"study,":[63],"we":[64],"propose":[65],"Multi-Programming":[66],"Language":[67],"Ensemble":[68],"(MPLE),":[69],"novel":[71],"ensemble-based":[72],"method":[73,104],"utilizes":[75],"generation":[77,91,155],"multiple":[79],"languages":[81],"to":[82,125,152,170],"enhance":[83],"overall":[84],"performance.":[85],"By":[86],"treating":[87],"each":[88],"language-specific":[89,106],"process":[92],"as":[93,143],"an":[94],"individual":[95],"\"weak":[96],"expert\"":[97],"and":[98,108,129,147,176],"effectively":[99],"integrating":[100],"their":[101],"outputs,":[102],"our":[103,162],"mitigates":[105],"biases.":[109],"This":[110],"ensemble":[112],"strategy":[113],"leverages":[114],"complementary":[116],"strengths":[117],"enabling":[122],"model":[124],"produce":[126],"accurate":[128],"code.":[131],"Our":[132],"can":[134],"seamlessly":[136],"integrated":[137],"with":[138,178],"commonly":[139],"used":[140],"techniques":[141],"such":[142],"reflection":[145],"algorithm":[146],"Monte":[148],"Carlo":[149],"tree":[150],"search":[151],"improve":[153],"quality":[156],"further.":[157],"Experimental":[158],"results":[159,192],"show":[160],"framework":[163],"consistently":[164],"enhances":[165],"baseline":[166],"performance":[167],"up":[169],"17.92%":[171],"benchmarks":[174],"(HumanEval":[175],"HumanEval-plus),":[177],"standout":[180],"result":[181],"96.25%":[183],"accuracy":[184],"HumanEval":[187],"benchmark,":[188],"achieving":[189],"new":[190],"state-of-the-art":[191],"various":[194],"LLM":[195],"models.":[196],"The":[197],"will":[199],"released":[201],"at":[202],"https://github.com/NinjaTech-AI/MPLE":[203]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":5}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-10-21T00:00:00"}