{"id":"https://openalex.org/W7163710186","doi":"https://doi.org/10.48550/arxiv.2606.05836","title":"ProSPy: A Profiling-Driven SQL-Python Agentic Framework for Enterprise Text-to-SQL","display_name":"ProSPy: A Profiling-Driven SQL-Python Agentic Framework for Enterprise Text-to-SQL","publication_year":2026,"publication_date":"2026-06-04","ids":{"openalex":"https://openalex.org/W7163710186","doi":"https://doi.org/10.48550/arxiv.2606.05836"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.05836","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05836","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":null,"license_id":null,"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.2606.05836","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137947402","display_name":"Zhaorui Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zhaorui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137364858","display_name":"Huawei Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Huawei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137938569","display_name":"Sen Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Sen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137953334","display_name":"Yuhui Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yuhui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137983068","display_name":"Haoxuan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Haoxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137996750","display_name":"Zhizhen Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Zhizhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137997029","display_name":"Xuan Yi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi, Xuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027864980","display_name":"Chen Hou","orcid":"https://orcid.org/0000-0002-8558-5655"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hou, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137963030","display_name":"Defeng Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Defeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138008329","display_name":"Chao Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Chao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137931398","display_name":"Minfeng Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Minfeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138000154","display_name":"Dazhen Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Dazhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137936790","display_name":"Haozhe Feng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Feng, Haozhe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137972737","display_name":"Danqing Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Danqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138003422","display_name":"Yingcai Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yingcai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137932171","display_name":"Peng Chen","orcid":"https://orcid.org/0000-0001-6503-1113"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137955417","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0002-8814-1005"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Wei","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/T10181","display_name":"Natural Language Processing Techniques","score":0.29589998722076416,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.29589998722076416,"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/T10028","display_name":"Topic Modeling","score":0.08349999785423279,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.051100000739097595,"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/sql","display_name":"SQL","score":0.771399974822998},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.5914000272750854},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.48429998755455017},{"id":"https://openalex.org/keywords/stored-procedure","display_name":"Stored procedure","score":0.4717999994754791},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.45730000734329224},{"id":"https://openalex.org/keywords/language-integrated-query","display_name":"Language Integrated Query","score":0.45089998841285706},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.44999998807907104},{"id":"https://openalex.org/keywords/sql-injection","display_name":"SQL injection","score":0.42730000615119934},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4138000011444092}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8145999908447266},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.771399974822998},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.5914000272750854},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.5188999772071838},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.48429998755455017},{"id":"https://openalex.org/C154420247","wikidata":"https://www.wikidata.org/wiki/Q846619","display_name":"Stored procedure","level":5,"score":0.4717999994754791},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C179531526","wikidata":"https://www.wikidata.org/wiki/Q595637","display_name":"Language Integrated Query","level":5,"score":0.45089998841285706},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.44999998807907104},{"id":"https://openalex.org/C150451098","wikidata":"https://www.wikidata.org/wiki/Q506059","display_name":"SQL injection","level":5,"score":0.42730000615119934},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4138000011444092},{"id":"https://openalex.org/C55596503","wikidata":"https://www.wikidata.org/wiki/Q1431648","display_name":"Data definition language","level":3,"score":0.40700000524520874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3727000057697296},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.3709000051021576},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3379000127315521},{"id":"https://openalex.org/C167544706","wikidata":"https://www.wikidata.org/wiki/Q360842","display_name":"SQL/PSM","level":5,"score":0.33250001072883606},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C30775581","wikidata":"https://www.wikidata.org/wiki/Q632285","display_name":"Database schema","level":3,"score":0.32199999690055847},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C33882796","wikidata":"https://www.wikidata.org/wiki/Q4826222","display_name":"Autocommit","level":5,"score":0.30640000104904175},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2711000144481659},{"id":"https://openalex.org/C194222762","wikidata":"https://www.wikidata.org/wiki/Q114486","display_name":"Query by Example","level":4,"score":0.25929999351501465},{"id":"https://openalex.org/C141589383","wikidata":"https://www.wikidata.org/wiki/Q644775","display_name":"Data Transformation Services","level":5,"score":0.2567000091075897},{"id":"https://openalex.org/C47487241","wikidata":"https://www.wikidata.org/wiki/Q5227230","display_name":"Data access","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.05836","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05836","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.05836","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05836","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":null,"license_id":null,"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":{"Large":[0],"language":[1],"models":[2],"have":[3],"substantially":[4],"advanced":[5],"Text-to-SQL":[6],"systems,":[7],"yet":[8],"applying":[9],"them":[10],"to":[11,36,165],"enterprise-scale":[12,56],"databases":[13,17,107],"remains":[14],"challenging.":[15],"Real-world":[16],"often":[18],"contain":[19],"large":[20,77,106],"and":[21,29,90,120,130,143,151,169,177],"heterogeneous":[22],"schemas,":[23],"incomplete":[24],"metadata,":[25],"dialect-specific":[26],"SQL":[27,41,88,104,124,166],"syntax,":[28],"complex":[30],"analytical":[31],"questions":[32],"that":[33,134,161],"are":[34],"difficult":[35],"solve":[37],"with":[38,96,108,140,153],"a":[39,50,86,171],"single":[40],"query.":[42],"To":[43],"address":[44],"these":[45],"challenges,":[46],"we":[47],"propose":[48],"ProSPy,":[49],"Profiling-driven":[51],"SQL--Python":[52],"agentic":[53],"framework":[54],"for":[55],"Text-to-SQL.":[57],"ProSPy":[58,135,162],"structures":[59],"the":[60,101,109],"reasoning":[61],"process":[62],"into":[63,79],"four":[64],"stages:":[65],"it":[66],"first":[67],"extracts":[68],"fine-grained":[69],"data":[70],"evidence":[71],"through":[72,85],"automatic":[73],"profiling,":[74],"progressively":[75],"prunes":[76],"schemas":[78],"task-relevant":[80],"contexts,":[81],"fetches":[82],"intermediate":[83],"views":[84],"dialect-agnostic":[87],"interface,":[89],"finally":[91],"performs":[92],"flexible":[93],"downstream":[94],"analysis":[95,159],"Python.":[97],"This":[98],"design":[99],"combines":[100],"efficiency":[102],"of":[103,111,149],"over":[105],"flexibility":[110],"Python-based":[112],"analysis,":[113],"while":[114],"reducing":[115],"reliance":[116],"on":[117,127],"unreliable":[118],"metadata":[119],"improving":[121],"robustness":[122],"across":[123],"dialects.":[125],"Experiments":[126],"Spider":[128,131],"2.0-Lite":[129],"2.0-Snow":[132],"show":[133],"consistently":[136],"outperforms":[137],"strong":[138],"baselines":[139],"both":[141],"open-source":[142],"proprietary":[144],"models,":[145],"achieving":[146],"execution":[147],"accuracies":[148],"60.15%":[150],"60.51%":[152],"Claude-4.5-Opus,":[154],"without":[155],"majority":[156],"voting.":[157],"Further":[158],"shows":[160],"is":[163],"robust":[164],"dialect":[167],"variations":[168],"achieves":[170],"favorable":[172],"trade-off":[173],"between":[174],"schema":[175],"recall":[176],"precision.":[178]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-06T00:00:00"}
