{"id":"https://openalex.org/W7165663995","doi":"https://doi.org/10.48550/arxiv.2606.23537","title":"SQLConductor: Search-to-Policy Learning for Step-wise Text-to-SQL Orchestration","display_name":"SQLConductor: Search-to-Policy Learning for Step-wise Text-to-SQL Orchestration","publication_year":2026,"publication_date":"2026-06-22","ids":{"openalex":"https://openalex.org/W7165663995","doi":"https://doi.org/10.48550/arxiv.2606.23537"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.23537","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.23537","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.23537","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021436608","display_name":"Y C Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Yizhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063263224","display_name":"Zhangyang Peng","orcid":"https://orcid.org/0009-0002-5383-9750"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Zhangyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139128857","display_name":"Boyan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Boyan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139160552","display_name":"Yuyu Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Yuyu","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":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/T10317","display_name":"Advanced Database Systems and Queries","score":0.3447999954223633,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.3447999954223633,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11986","display_name":"Scientific Computing and Data Management","score":0.1242000013589859,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.07360000163316727,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/orchestration","display_name":"Orchestration","score":0.8744000196456909},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.692300021648407},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6225000023841858},{"id":"https://openalex.org/keywords/executable","display_name":"Executable","score":0.4927999973297119},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.48069998621940613},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.45910000801086426},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4194999933242798},{"id":"https://openalex.org/keywords/commit","display_name":"Commit","score":0.35580000281333923}],"concepts":[{"id":"https://openalex.org/C199168358","wikidata":"https://www.wikidata.org/wiki/Q3367000","display_name":"Orchestration","level":3,"score":0.8744000196456909},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.847100019454956},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.692300021648407},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6225000023841858},{"id":"https://openalex.org/C160145156","wikidata":"https://www.wikidata.org/wiki/Q778586","display_name":"Executable","level":2,"score":0.4927999973297119},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.48069998621940613},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.45910000801086426},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4194999933242798},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4180999994277954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4083000123500824},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3955000042915344},{"id":"https://openalex.org/C153180980","wikidata":"https://www.wikidata.org/wiki/Q19776675","display_name":"Commit","level":2,"score":0.35580000281333923},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3411000072956085},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.323199987411499},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.29760000109672546},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2904999852180481},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.26809999346733093},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C49020025","wikidata":"https://www.wikidata.org/wiki/Q1059099","display_name":"Chaining","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.23537","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.23537","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.23537","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.23537","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Text-to-SQL":[0,100,225],"enables":[1],"users":[2],"to":[3,16,47,71,80,113,138,145,158,236],"access":[4],"relational":[5],"databases":[6],"via":[7],"natural":[8],"language,":[9],"but":[10,65],"real-world":[11],"settings":[12],"remain":[13],"challenging":[14],"due":[15],"coordinated":[17],"reasoning":[18,30],"over":[19],"complex":[20],"database":[21],"environments.":[22],"Existing":[23],"systems":[24],"often":[25],"use":[26],"multi-stage":[27],"pipelines":[28,38],"or":[29,223],"models":[31],"specialized":[32,60,103],"for":[33,62,96,105,179],"individual":[34],"stages.":[35],"However,":[36],"fixed":[37],"rely":[39],"on":[40,119,186,204],"predefined":[41],"stage":[42],"orders,":[43],"limiting":[44],"their":[45],"adaptivity":[46],"query":[48,238],"demands":[49],"and":[50,77,83,108,122,142,163,188,198],"intermediate":[51,81,120],"evidence.":[52],"Recent":[53],"orchestration-based":[54],"methods":[55,218],"provide":[56],"flexibility":[57],"by":[58],"composing":[59],"modules":[61],"each":[63],"query,":[64],"typical":[66],"plan-then-execute":[67],"approaches":[68],"still":[69],"commit":[70],"a":[72,91,110,176,207],"complete":[73],"workflow":[74,106,173],"before":[75],"execution":[76,196],"cannot":[78],"adapt":[79],"artifacts":[82,121],"feedback.":[84,123],"In":[85],"this":[86,126],"paper,":[87],"we":[88],"propose":[89],"SQLConductor,":[90],"step-wise":[92,180],"orchestration":[93,161,181,209,235],"learning":[94],"framework":[95],"Text-to-SQL.":[97],"SQLConductor":[98,128,193],"formulates":[99],"subtasks":[101],"as":[102],"actions":[104],"composition":[107],"trains":[109],"policy":[111,150,178,210,233],"model":[112,151],"select":[114],"the":[115,231],"next":[116],"action":[117,214],"based":[118],"To":[124],"learn":[125],"policy,":[127],"introduces":[129],"Search-to-Policy":[130],"Learning,":[131],"which":[132],"uses":[133],"Monte":[134],"Carlo":[135],"Tree":[136],"Search":[137],"explore":[139],"candidate":[140],"workflows":[141],"stability":[143],"estimation":[144],"identify":[146],"robust":[147],"supervision.":[148],"The":[149],"is":[152],"trained":[153],"with":[154,206],"Stability-weighted":[155],"Supervised":[156],"Fine-tuning":[157],"prioritize":[159],"high-quality":[160],"patterns":[162],"further":[164],"enhanced":[165],"through":[166],"Curriculum":[167],"Reinforcement":[168],"Learning.":[169],"This":[170],"transforms":[171],"offline":[172],"search":[174],"into":[175],"deployable":[177],"at":[182],"inference":[183],"time.":[184],"Experiments":[185],"BIRD-Dev":[187,205],"out-of-distribution":[189],"datasets":[190],"show":[191,229],"that":[192,219,230],"achieves":[194],"superior":[195],"accuracy":[197],"strong":[199],"generalization,":[200],"reaching":[201],"73.2%":[202],"EX":[203],"compact":[208],"coordinating":[211],"frozen":[212],"larger":[213,224],"models,":[215],"outperforming":[216],"prior":[217],"directly":[220],"train":[221],"comparable":[222],"backbones.":[226],"Further":[227],"analyses":[228],"learned":[232],"adapts":[234],"diverse":[237],"demands.":[239]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-24T00:00:00"}
