{"id":"https://openalex.org/W7135028680","doi":"https://doi.org/10.48550/arxiv.2603.10697","title":"EvoSchema: Towards Text-to-SQL Robustness Against Schema Evolution","display_name":"EvoSchema: Towards Text-to-SQL Robustness Against Schema Evolution","publication_year":2026,"publication_date":"2026-03-11","ids":{"openalex":"https://openalex.org/W7135028680","doi":"https://doi.org/10.48550/arxiv.2603.10697"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10697","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10697","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.10697","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079828360","display_name":"Tianshu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Zhang, Tianshu","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128850709","display_name":"Kun Qian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian, Kun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119538797","display_name":"Siddhartha Sahai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sahai, Siddhartha","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128844979","display_name":"Yuan Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Yuan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074090487","display_name":"Shaddy Garg","orcid":"https://orcid.org/0000-0002-4375-9776"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Garg, Shaddy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128825635","display_name":"Huan Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Huan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128848135","display_name":"Yunyao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yunyao","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5079828360"],"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":0.34610000252723694,"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":0.34610000252723694,"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":0.2061000019311905,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.08829999715089798,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/database-schema","display_name":"Database schema","score":0.7017999887466431},{"id":"https://openalex.org/keywords/schema-migration","display_name":"Schema migration","score":0.6657999753952026},{"id":"https://openalex.org/keywords/schema","display_name":"Schema (genetic algorithms)","score":0.5482000112533569},{"id":"https://openalex.org/keywords/semi-structured-model","display_name":"Semi-structured model","score":0.5415999889373779},{"id":"https://openalex.org/keywords/schema-evolution","display_name":"Schema evolution","score":0.5060999989509583},{"id":"https://openalex.org/keywords/conceptual-schema","display_name":"Conceptual schema","score":0.49300000071525574},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48820000886917114}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7372000217437744},{"id":"https://openalex.org/C30775581","wikidata":"https://www.wikidata.org/wiki/Q632285","display_name":"Database schema","level":3,"score":0.7017999887466431},{"id":"https://openalex.org/C153440673","wikidata":"https://www.wikidata.org/wiki/Q7431119","display_name":"Schema migration","level":5,"score":0.6657999753952026},{"id":"https://openalex.org/C52146309","wikidata":"https://www.wikidata.org/wiki/Q7431116","display_name":"Schema (genetic algorithms)","level":2,"score":0.5482000112533569},{"id":"https://openalex.org/C56310702","wikidata":"https://www.wikidata.org/wiki/Q2269281","display_name":"Semi-structured model","level":4,"score":0.5415999889373779},{"id":"https://openalex.org/C2780660560","wikidata":"https://www.wikidata.org/wiki/Q3951893","display_name":"Schema evolution","level":4,"score":0.5060999989509583},{"id":"https://openalex.org/C29275276","wikidata":"https://www.wikidata.org/wiki/Q2268965","display_name":"Conceptual schema","level":3,"score":0.49300000071525574},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48820000886917114},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.4788999855518341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4146000146865845},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C150012506","wikidata":"https://www.wikidata.org/wiki/Q6031185","display_name":"Information schema","level":5,"score":0.3653999865055084},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34700000286102295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3305000066757202},{"id":"https://openalex.org/C190703929","wikidata":"https://www.wikidata.org/wiki/Q1331138","display_name":"Star schema","level":4,"score":0.30469998717308044},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2687000036239624}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10697","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10697","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.10697","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10697","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":"article"},"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":{"Neural":[0],"text-to-SQL":[1,120,188],"models,":[2],"which":[3,78,225],"translate":[4],"natural":[5],"language":[6],"questions":[7,219],"(NLQs)":[8],"into":[9,243],"SQL":[10],"queries":[11],"given":[12],"a":[13,63,109,128,169,247],"database":[14,21,88,148,197],"schema,":[15],"have":[16,168],"achieved":[17],"remarkable":[18,227],"performance.":[19],"However,":[20],"schemas":[22],"frequently":[23],"evolve":[24],"to":[25,34,68,113,177,211,220,230],"meet":[26],"new":[27],"requirements.":[28],"Such":[29],"schema":[30,76,89,104,124,130,205,214],"evolution":[31,131],"often":[32],"leads":[33],"performance":[35,175],"degradation":[36],"for":[37,216,250],"models":[38,200],"trained":[39,201,232],"on":[40,48,173,202,233,236],"static":[41],"schemas.":[42,149],"Existing":[43],"work":[44],"either":[45],"mainly":[46],"focuses":[47],"simply":[49],"paraphrasing":[50],"some":[51],"syntactic":[52],"or":[53,61],"semantic":[54],"mappings":[55],"among":[56],"NLQ,":[57],"DB":[58],"and":[59,65,86,115,139,161,196,246],"SQL,":[60],"lacks":[62],"comprehensive":[64,110],"controllable":[66],"way":[67],"investigate":[69],"the":[70,75,83,95,100,117,144,183,209,213,217],"model":[71,174,194,210,244],"robustness":[72,118,228],"issue":[73],"under":[74,122],"evolution,":[77,105],"is":[79],"insufficient":[80],"when":[81],"facing":[82],"increasingly":[84],"complex":[85],"rich":[87],"changes":[90],"in":[91,94,190,256],"reality,":[92],"especially":[93],"LLM":[96],"era.":[97],"To":[98],"address":[99],"challenges":[101],"posed":[102],"by":[103],"we":[106,152],"present":[107],"EvoSchema,":[108,151],"benchmark":[111,239],"designed":[112],"assess":[114],"enhance":[116],"of":[119,147,185,192,254],"systems":[121,252],"real-world":[123,258],"changes.":[125,179],"EvoSchema":[126,181],"introduces":[127],"novel":[129],"taxonomy,":[132],"encompassing":[133],"ten":[134],"perturbation":[135],"types":[136],"across":[137],"columnlevel":[138],"table-level":[140,166],"modifications,":[141],"systematically":[142],"simulating":[143],"dynamic":[145],"nature":[146],"Through":[150],"conduct":[153],"an":[154],"in-depth":[155],"evaluation":[156],"spanning":[157],"different":[158],"open":[159],"source":[160],"closed-source":[162],"LLMs,":[163],"revealing":[164],"that":[165],"perturbations":[167],"significantly":[170],"greater":[171],"impact":[172],"compared":[176,229],"column-level":[178],"Furthermore,":[180],"inspires":[182],"development":[184],"more":[186],"resilient":[187],"systems,":[189],"terms":[191],"both":[193],"training":[195],"design.":[198],"The":[199],"EvoSchema's":[203],"diverse":[204],"designs":[206],"can":[207],"force":[208],"distinguish":[212],"difference":[215],"same":[218],"avoid":[221],"learning":[222],"spurious":[223],"patterns,":[224],"demonstrate":[226],"those":[231],"unperturbed":[234],"data":[235],"average.":[237],"This":[238],"offers":[240],"valuable":[241],"insights":[242],"behavior":[245],"path":[248],"forward":[249],"designing":[251],"capable":[253],"thriving":[255],"dynamic,":[257],"environments.":[259]},"counts_by_year":[],"updated_date":"2026-03-13T14:25:03.468858","created_date":"2026-03-13T00:00:00"}
