{"id":"https://openalex.org/W7133988234","doi":"https://doi.org/10.48550/arxiv.2603.03742","title":"ErrorLLM: Modeling SQL Errors for Text-to-SQL Refinement","display_name":"ErrorLLM: Modeling SQL Errors for Text-to-SQL Refinement","publication_year":2026,"publication_date":"2026-03-04","ids":{"openalex":"https://openalex.org/W7133988234","doi":"https://doi.org/10.48550/arxiv.2603.03742"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.03742","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101383081","display_name":"Zijin Hong","orcid":"https://orcid.org/0009-0008-2283-255X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Zijin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128158793","display_name":"Hao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128160331","display_name":"Zheng Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan, Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128181684","display_name":"Qinggang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Qinggang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128130512","display_name":"Luyao Zhuang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhuang, Luyao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128165681","display_name":"Qing Liao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liao, Qing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033233243","display_name":"Feiran Huang","orcid":"https://orcid.org/0000-0003-4294-0212"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Feiran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128202558","display_name":"Yangqiu Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Yangqiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128150220","display_name":"Xiao Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Xiao","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/T11986","display_name":"Scientific Computing and Data Management","score":0.19329999387264252,"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"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.19329999387264252,"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/T12479","display_name":"Web Application Security Vulnerabilities","score":0.1859000027179718,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10260","display_name":"Software Engineering Research","score":0.07180000096559525,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/debugging","display_name":"Debugging","score":0.6697999835014343},{"id":"https://openalex.org/keywords/sql","display_name":"SQL","score":0.647599995136261},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.4846000075340271},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.3847000002861023},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.37470000982284546},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3531999886035919},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.3343000113964081}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8880000114440918},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.6697999835014343},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.647599995136261},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.5860999822616577},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.4846000075340271},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4535999894142151},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.3847000002861023},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.37470000982284546},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.334199994802475},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33070001006126404},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.30970001220703125},{"id":"https://openalex.org/C55596503","wikidata":"https://www.wikidata.org/wiki/Q1431648","display_name":"Data definition language","level":3,"score":0.2935999929904938},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2847000062465668},{"id":"https://openalex.org/C154420247","wikidata":"https://www.wikidata.org/wiki/Q846619","display_name":"Stored procedure","level":5,"score":0.2825999855995178},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.2531000077724457},{"id":"https://openalex.org/C194222762","wikidata":"https://www.wikidata.org/wiki/Q114486","display_name":"Query by Example","level":4,"score":0.2502000033855438}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.03742","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.03742","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.03742","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":"pmh:doi:10.48550/arxiv.2603.03742","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.767612099647522,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"the":[1,72,80,117,166,180,188,200],"remarkable":[2],"performance":[3],"of":[4,74],"large":[5],"language":[6],"models":[7,104],"(LLMs)":[8],"in":[9,35,79],"text-to-SQL":[10,105,112],"(SQL":[11],"generation),":[12],"correctly":[13],"producing":[14],"SQL":[15,23,37,189],"queries":[16],"remains":[17],"challenging":[18],"during":[19],"initial":[20,206],"generation.":[21,207],"The":[22],"refinement":[24,186,216,230],"task":[25],"is":[26],"subsequently":[27],"introduced":[28],"to":[29,71,129,168],"correct":[30,92],"syntactic":[31],"and":[32,82,84,120,133,136,218],"semantic":[33,139,149],"errors":[34,58,161,172],"generated":[36],"queries.":[38],"However,":[39],"existing":[40],"paradigms":[41],"face":[42],"two":[43],"major":[44],"limitations:":[45],"(i)":[46],"self-debugging":[47],"becomes":[48],"increasingly":[49],"ineffective":[50],"as":[51,123],"modern":[52],"LLMs":[53],"rarely":[54],"produce":[55],"explicit":[56,75],"execution":[57,131],"that":[59,89,102,145,197,211],"can":[60],"trigger":[61],"debugging":[62],"signals;":[63],"(ii)":[64],"self-correction":[65],"exhibits":[66],"low":[67],"detection":[68,128,212,225],"precision":[69],"due":[70],"lack":[73],"error":[76,143,150,176],"modeling":[77],"grounded":[78],"question":[81,119],"schema,":[83],"suffers":[85],"from":[86],"severe":[87],"hallucination":[88],"frequently":[90],"corrupts":[91],"SQLs.":[93],"In":[94],"this":[95],"paper,":[96],"we":[97,115,157,183],"propose":[98],"ErrorLLM,":[99],"a":[100,108,153],"framework":[101],"explicitly":[103,158],"Errors":[106],"within":[107],"dedicated":[109,142,175],"LLM":[110,167],"for":[111],"refinement.":[113],"Specifically,":[114],"represent":[116],"user":[118],"database":[121],"schema":[122],"structural":[124,163],"features,":[125],"employ":[126],"static":[127],"identify":[130],"failures":[132],"surface":[134],"mismatches,":[135],"extend":[137],"ErrorLLM's":[138],"space":[140],"with":[141,162],"tokens":[144],"capture":[146],"categorized":[147],"implicit":[148,171],"types.":[151],"Through":[152],"well-designed":[154],"training":[155],"strategy,":[156],"model":[159],"these":[160],"representations,":[164],"enabling":[165],"detect":[169],"complex":[170],"by":[173,179,191,223],"predicting":[174],"tokens.":[177],"Guided":[178],"detected":[181],"errors,":[182],"perform":[184],"error-guided":[185],"on":[187],"structure":[190],"prompting":[192],"LLMs.":[193],"Extensive":[194],"experiments":[195],"demonstrate":[196],"ErrorLLM":[198,219],"achieves":[199],"most":[201],"significant":[202],"improvements":[203],"over":[204],"backbone":[205],"Further":[208],"analysis":[209],"reveals":[210],"quality":[213],"directly":[214],"determines":[215],"effectiveness,":[217],"addresses":[220],"both":[221],"sides":[222],"high":[224],"F1":[226],"score":[227],"while":[228],"maintain":[229],"effectiveness.":[231]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-06T00:00:00"}
