{"id":"https://openalex.org/W4416034059","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.1079","title":"MultiLingPoT: Boosting Mathematical Reasoning in LLMs through Multilingual Program Integration","display_name":"MultiLingPoT: Boosting Mathematical Reasoning in LLMs through Multilingual Program Integration","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416034059","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.1079"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.1079","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.1079","pdf_url":"https://aclanthology.org/2025.findings-emnlp.1079.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.1079.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113174784","display_name":"Nianqi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nianqi Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031164256","display_name":"Zujie Liang","orcid":"https://orcid.org/0009-0002-9736-0231"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zujie Liang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103134216","display_name":"Siyu Yuan","orcid":"https://orcid.org/0009-0004-4439-0984"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siyu Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075507821","display_name":"Jiaqing Liang","orcid":"https://orcid.org/0000-0003-0670-5602"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiaqing Liang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081703144","display_name":"Wei Feng","orcid":"https://orcid.org/0000-0002-9993-8722"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5110850309","display_name":"Yanghua Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yanghua Xiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31115117,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"19794","last_page":"19811"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.7516000270843506,"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"}},"topics":[{"id":"https://openalex.org/T13523","display_name":"Mathematics, Computing, and Information Processing","score":0.7516000270843506,"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"}},{"id":"https://openalex.org/T10126","display_name":"Logic, programming, and type systems","score":0.05900000035762787,"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/T11435","display_name":"Polynomial and algebraic computation","score":0.02800000086426735,"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/boosting","display_name":"Boosting (machine learning)","score":0.7301999926567078},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.3903999924659729},{"id":"https://openalex.org/keywords/case-based-reasoning","display_name":"Case-based reasoning","score":0.3312999904155731},{"id":"https://openalex.org/keywords/knowledge-representation-and-reasoning","display_name":"Knowledge representation and reasoning","score":0.2549000084400177}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7301999926567078},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5738999843597412},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48570001125335693},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3912000060081482},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C20162079","wikidata":"https://www.wikidata.org/wiki/Q1151406","display_name":"Case-based reasoning","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.31520000100135803},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.28439998626708984},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26089999079704285},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.1079","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.1079","pdf_url":"https://aclanthology.org/2025.findings-emnlp.1079.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.1079","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.1079","pdf_url":"https://aclanthology.org/2025.findings-emnlp.1079.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416034059.pdf","grobid_xml":"https://content.openalex.org/works/W4416034059.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Program-of-Thought,":[0],"which":[1],"aims":[2],"to":[3,18,32,82,108],"use":[4,33],"program":[5],"instead":[6],"of":[7,70],"natural":[8,31],"language":[9,37,48,116,130,143],"in":[10,26,73,133],"reasoning,":[11],"is":[12,30],"an":[13],"important":[14],"way":[15],"for":[16,38],"LLMs":[17],"solve":[19],"mathematical":[20],"problems.Since":[21],"different":[22,27],"programming":[23,54],"languages":[24,87],"excel":[25],"areas,":[28],"it":[29],"the":[34,51,68,74,80,110,113],"most":[35,114],"suitable":[36,115],"solving":[39],"specific":[40],"problems.However,":[41],"current":[42],"research":[43],"only":[44],"focuses":[45],"on":[46,90],"single":[47],"PoT,":[49],"ignoring":[50],"differences":[52,131],"between":[53],"languages.Therefore,":[55],"this":[56],"paper":[57],"proposes":[58],"a":[59],"multilingual":[60,71,91],"programme":[61],"reasoning":[62,97],"method,":[63],"MultiLingPoT,":[64],"and":[65,76,93,102,119,136],"deeply":[66],"explores":[67],"impact":[69],"integration":[72],"training":[75],"inference.This":[77],"method":[78],"allows":[79],"model":[81,111],"answer":[83],"questions":[84],"using":[85],"multiple":[86],"by":[88,99],"fine-tuning":[89],"data":[92],"improving":[94],"individual":[95],"language's":[96],"accuracy":[98],"2.5%.Additionally,":[100],"prior":[101],"posterior":[103],"selection":[104],"methods":[105],"are":[106],"used":[107],"help":[109],"select":[112],"during":[117],"inference,":[118],"achieves":[120],"8%":[121],"performance":[122],"gains.Finally,":[123],"our":[124],"code":[125,147],"metric":[126],"analysis":[127],"shows":[128],"that":[129],"manifest":[132],"encapsulation":[134],"levels":[135],"implementation":[137],"granularity,":[138],"while":[139],"strategic":[140],"deviation":[141],"from":[142],"conventions":[144],"can":[145],"enhances":[146],"performance.":[148],"1":[149]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-08T00:00:00"}
