{"id":"https://openalex.org/W7128697384","doi":"https://doi.org/10.48448/1ab3-kh97","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":"2026-01-07","ids":{"openalex":"https://openalex.org/W7128697384","doi":"https://doi.org/10.48448/1ab3-kh97"},"language":"en","primary_location":{"id":"doi:10.48448/1ab3-kh97","doi":"https://doi.org/10.48448/1ab3-kh97","is_oa":true,"landing_page_url":"https://doi.org/10.48448/1ab3-kh97","pdf_url":null,"source":{"id":"https://openalex.org/S7407053148","display_name":"Underline Science Inc.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Audiovisual"},"volume":null,"type":"other","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48448/1ab3-kh97","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125741655","display_name":"Association for Artificial Intelligence 2026","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Association for Artificial Intelligence 2026","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125711462","display_name":"Gang Chen","orcid":null,"observed_orcids":[]},"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":"Chen, Gang","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125720833","display_name":"Xiaojin Fu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fu, Xiaojin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125755819","display_name":"Shisi Guan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Shisi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011272312","display_name":"Xiongwei Han","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han, Xiongwei","raw_affiliation_strings":["Huawei"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116306928","display_name":"Zehua Liu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zehua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125748706","display_name":"Yuan Wang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125691018","display_name":"Han Wu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wu, Han","raw_affiliation_strings":["City University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125736597","display_name":"Ziyang Xiao","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Ziyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067767221","display_name":"Jingrong Xie","orcid":"https://orcid.org/0000-0002-8360-1535","observed_orcids":["https://orcid.org/0000-0002-8360-1535","https://orcid.org/0009-0004-4795-4239"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Jingrong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125723648","display_name":"Lilin Xu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xu, Lilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125757919","display_name":"Wing-Yin Yu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Wing-Yin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125712478","display_name":"Dongxiang Zhang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Dongxiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5125765080","display_name":"Jingyan Zhu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Jingyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T10028","display_name":"Topic Modeling","score":0.5351999998092651,"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/T10028","display_name":"Topic Modeling","score":0.5351999998092651,"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/T13904","display_name":"Artificial Intelligence Applications","score":0.10649999976158142,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.05550000071525574,"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/optimization-modeling","display_name":"optimization modeling","score":0.925000011920929},{"id":"https://openalex.org/keywords/supervised-fine-tuning","display_name":"supervised fine-tuning","score":0.8339999914169312},{"id":"https://openalex.org/keywords/deepseek-r1","display_name":"DeepSeek-R1","score":0.6349999904632568},{"id":"https://openalex.org/keywords/automated-decision-making","display_name":"automated decision-making","score":0.4189999997615814}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7608000040054321},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.722000002861023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5934000015258789},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.5175999999046326},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.48730000853538513},{"id":"https://openalex.org/C195344581","wikidata":"https://www.wikidata.org/wiki/Q2555318","display_name":"Automated reasoning","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46209999918937683},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.4034999907016754},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.32120001316070557},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3107999861240387},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C37335422","wikidata":"https://www.wikidata.org/wiki/Q6888134","display_name":"Model-based reasoning","level":3,"score":0.2955000102519989},{"id":"https://openalex.org/C89288958","wikidata":"https://www.wikidata.org/wiki/Q7301504","display_name":"Reasoning system","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C86827895","wikidata":"https://www.wikidata.org/wiki/Q7098582","display_name":"Opportunistic reasoning","level":4,"score":0.27399998903274536},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2721000015735626}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48448/1ab3-kh97","doi":"https://doi.org/10.48448/1ab3-kh97","is_oa":true,"landing_page_url":"https://doi.org/10.48448/1ab3-kh97","pdf_url":null,"source":{"id":"https://openalex.org/S7407053148","display_name":"Underline Science Inc.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Audiovisual"}],"best_oa_location":{"id":"doi:10.48448/1ab3-kh97","doi":"https://doi.org/10.48448/1ab3-kh97","is_oa":true,"landing_page_url":"https://doi.org/10.48448/1ab3-kh97","pdf_url":null,"source":{"id":"https://openalex.org/S7407053148","display_name":"Underline Science Inc.","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Audiovisual"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7128687850","https://openalex.org/W4416617077","https://openalex.org/W4416235990","https://openalex.org/W4417300000","https://openalex.org/W4414886187","https://openalex.org/W4414971175","https://openalex.org/W7165951618","https://openalex.org/W4417528486","https://openalex.org/W7101916501","https://openalex.org/W7126048685"],"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":"2026-10-28T10:33:24.094632","created_date":"2026-02-13T00:00:00"}