{"id":"https://openalex.org/W7139095591","doi":"https://doi.org/10.1609/aaai.v40i40.40699","title":"DeepOR: A Deep Reasoning Foundation Model for Optimization Modeling","display_name":"DeepOR: A Deep Reasoning Foundation Model for Optimization Modeling","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7139095591","doi":"https://doi.org/10.1609/aaai.v40i40.40699"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i40.40699","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i40.40699","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40699/44660","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40699/44660","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101974883","display_name":"Ziyang Xiao","orcid":"https://orcid.org/0000-0002-3355-3379"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ziyang Xiao","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129891451","display_name":"Yuan Jessica Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I8696757","display_name":"Singapore University of Social Sciences","ror":"https://ror.org/01s57k749","country_code":"SG","type":"education","lineage":["https://openalex.org/I8696757"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yuan Jessica Wang","raw_affiliation_strings":["School of Business, Singapore University of Social Sciences"],"affiliations":[{"raw_affiliation_string":"School of Business, Singapore University of Social Sciences","institution_ids":["https://openalex.org/I8696757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129753289","display_name":"Xiongwei Han","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Xiongwei Han","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab"],"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125755819","display_name":"Shisi Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shisi Guan","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126713241","display_name":"Jingyan Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyan Zhu","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067767221","display_name":"Jingrong Xie","orcid":"https://orcid.org/0000-0002-8360-1535"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingrong Xie","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100780360","display_name":"Lilin Xu","orcid":"https://orcid.org/0009-0007-5203-7496"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lilin Xu","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025612495","display_name":"Hang Wu","orcid":"https://orcid.org/0000-0003-2724-7065"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Han Wu","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab"],"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081706999","display_name":"Wing-Yin Yu","orcid":"https://orcid.org/0000-0002-9559-1055"},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Wing Yin Yu","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab"],"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130079206","display_name":"Zehua Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Zehua Liu","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab"],"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111019871","display_name":"Xiaojin Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159102","display_name":"Huawei Technologies (Sweden)","ror":"https://ror.org/0500fyd17","country_code":"SE","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210159102"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Xiaojin Fu","raw_affiliation_strings":["Huawei Noah\u2019s Ark Lab"],"affiliations":[{"raw_affiliation_string":"Huawei Noah\u2019s Ark Lab","institution_ids":["https://openalex.org/I4210159102"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389238","display_name":"Gang Chen","orcid":"https://orcid.org/0000-0002-0124-2752"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Chen","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032211015","display_name":"Dongxiang Zhang","orcid":"https://orcid.org/0009-0006-6338-0698"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxiang Zhang","raw_affiliation_strings":["Zhejiang University"],"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":13,"corresponding_author_ids":["https://openalex.org/A5101974883"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.96537027,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"40","first_page":"34052","last_page":"34060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.11500000208616257,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.11500000208616257,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.09939999878406525,"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/T10028","display_name":"Topic Modeling","score":0.07649999856948853,"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/leverage","display_name":"Leverage (statistics)","score":0.7652000188827515},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.520799994468689},{"id":"https://openalex.org/keywords/automated-reasoning","display_name":"Automated reasoning","score":0.4970000088214874},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.47859999537467957},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.4047999978065491},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.4027000069618225},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.33320000767707825},{"id":"https://openalex.org/keywords/model-based-reasoning","display_name":"Model-based reasoning","score":0.31279999017715454}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7652000188827515},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239999771118164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6003000140190125},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.520799994468689},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.4970000088214874},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.47859999537467957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4546999931335449},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4027000069618225},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.33320000767707825},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.31279999017715454},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C86827895","wikidata":"https://www.wikidata.org/wiki/Q7098582","display_name":"Opportunistic reasoning","level":4,"score":0.2842000126838684},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.25940001010894775}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i40.40699","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i40.40699","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40699/44660","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i40.40699","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i40.40699","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/40699/44660","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.744959831237793,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7139095591.pdf","grobid_xml":"https://content.openalex.org/works/W7139095591.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Optimization":[0],"modeling":[1,25],"plays":[2],"a":[3,38,98,114,121],"critical":[4],"role":[5],"in":[6,51,63],"supporting":[7],"optimal":[8],"decision-making":[9],"across":[10],"various":[11],"domains.":[12],"Previous":[13],"works":[14],"have":[15,26,59],"demonstrated":[16],"that":[17,171],"large":[18],"language":[19],"models":[20,35],"(LLMs)":[21],"tailored":[22,144],"for":[23,81,145],"optimization":[24,82,146],"significantly":[27,175],"automated":[28],"and":[29,42,68,174],"simplified":[30],"this":[31,71],"process.":[32],"However,":[33],"these":[34],"typically":[36],"employ":[37,131],"straightforward":[39],"input-output":[40],"paradigm":[41],"struggle":[43],"with":[44,141,160],"challenging":[45],"instances.":[46],"In":[47,70],"contrast,":[48],"recent":[49],"advances":[50],"general-purpose":[52],"reasoning":[53,94,142,153],"LLMs":[54],"(RLLMs),":[55],"such":[56],"as":[57],"DeepSeek-R1,":[58],"shown":[60],"impressive":[61],"capabilities":[62,143],"complex":[64],"domains":[65],"like":[66],"mathematics":[67],"coding.":[69],"paper,":[72],"we":[73,104,130,155],"introduce":[74],"DeepOR,":[75],"the":[76,125,135,151],"first":[77],"RLLM":[78],"specifically":[79],"designed":[80],"modeling.":[83,147],"Instead":[84],"of":[85],"directly":[86],"outputting":[87],"solutions,":[88],"DeepOR":[89,172],"explicitly":[90],"performs":[91],"multiple":[92],"intermediate":[93],"steps.":[95],"To":[96,148],"adapt":[97],"base":[99,136],"LLM":[100,137],"into":[101],"an":[102],"RLLM,":[103],"begin":[105],"by":[106,113],"synthesizing":[107],"long":[108],"chain-of-thought":[109],"(CoT)":[110],"data":[111,127],"guided":[112],"flowchart,":[115],"which":[116],"is":[117],"automatically":[118],"generated":[119],"using":[120],"self-exploration":[122],"algorithm.":[123],"Once":[124],"training":[126],"are":[128],"prepared,":[129],"supervised":[132],"fine-tuning":[133],"on":[134,168],"to":[138],"endow":[139],"it":[140],"fully":[149],"leverage":[150],"model's":[152],"potential,":[154],"further":[156],"apply":[157],"reinforcement":[158],"learning":[159],"reward-shaping":[161],"derived":[162],"from":[163],"solver":[164],"feedback.":[165],"Experimental":[166],"results":[167],"benchmarks":[169],"confirm":[170],"consistently":[173],"outperforms":[176],"existing":[177],"state-of-the-art":[178],"approaches.":[179]},"counts_by_year":[],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2026-03-20T00:00:00"}