{"id":"https://openalex.org/W2891691255","doi":"https://doi.org/10.18653/v1/d18-1193","title":"SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task","display_name":"SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-Domain Text-to-SQL Task","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2891691255","doi":"https://doi.org/10.18653/v1/d18-1193","mag":"2891691255"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1193","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1193","pdf_url":"https://www.aclweb.org/anthology/D18-1193.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1193.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100664162","display_name":"Tao Yu","orcid":"https://orcid.org/0000-0003-2550-5008"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Yu","raw_affiliation_strings":["Department of Computer Science, Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005898634","display_name":"Michihiro Yasunaga","orcid":"https://orcid.org/0009-0003-3008-927X"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michihiro Yasunaga","raw_affiliation_strings":["Department of Computer Science, Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102720412","display_name":"Kai Yang","orcid":"https://orcid.org/0000-0002-3340-9377"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Yang","raw_affiliation_strings":["Department of Computer Science, Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421978","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-9418-0863"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["Department of Computer Science, Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433001","display_name":"Dongxu Wang","orcid":"https://orcid.org/0000-0002-4427-4412"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongxu Wang","raw_affiliation_strings":["Department of Computer Science, Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067424300","display_name":"Zifan Li","orcid":"https://orcid.org/0000-0002-0830-0740"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zifan Li","raw_affiliation_strings":["Department of Computer Science, Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081787254","display_name":"Dragomir Radev","orcid":"https://orcid.org/0000-0001-7830-6489"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dragomir Radev","raw_affiliation_strings":["Department of Computer Science, Yale University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Yale University","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I32971472"],"apc_list":null,"apc_paid":null,"fwci":17.067,"has_fulltext":true,"cited_by_count":200,"citation_normalized_percentile":{"value":0.9923755,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1653","last_page":"1663"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9994999766349792,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9872000217437744,"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/computer-science","display_name":"Computer science","score":0.8982225656509399},{"id":"https://openalex.org/keywords/sql","display_name":"SQL","score":0.7443628311157227},{"id":"https://openalex.org/keywords/stored-procedure","display_name":"Stored procedure","score":0.6703621745109558},{"id":"https://openalex.org/keywords/data-definition-language","display_name":"Data definition language","score":0.6318396925926208},{"id":"https://openalex.org/keywords/query-by-example","display_name":"Query by Example","score":0.594434916973114},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.5627453923225403},{"id":"https://openalex.org/keywords/sql-injection","display_name":"SQL injection","score":0.5186228156089783},{"id":"https://openalex.org/keywords/sql/psm","display_name":"SQL/PSM","score":0.46959128975868225},{"id":"https://openalex.org/keywords/data-transformation-services","display_name":"Data Transformation Services","score":0.4675033986568451},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.44556888937950134},{"id":"https://openalex.org/keywords/null","display_name":"Null (SQL)","score":0.4426635503768921},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4185056686401367},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41506507992744446},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3836877644062042},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.35218480229377747},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.2855715751647949}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8982225656509399},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.7443628311157227},{"id":"https://openalex.org/C154420247","wikidata":"https://www.wikidata.org/wiki/Q846619","display_name":"Stored procedure","level":5,"score":0.6703621745109558},{"id":"https://openalex.org/C55596503","wikidata":"https://www.wikidata.org/wiki/Q1431648","display_name":"Data definition language","level":3,"score":0.6318396925926208},{"id":"https://openalex.org/C194222762","wikidata":"https://www.wikidata.org/wiki/Q114486","display_name":"Query by Example","level":4,"score":0.594434916973114},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.5627453923225403},{"id":"https://openalex.org/C150451098","wikidata":"https://www.wikidata.org/wiki/Q506059","display_name":"SQL injection","level":5,"score":0.5186228156089783},{"id":"https://openalex.org/C167544706","wikidata":"https://www.wikidata.org/wiki/Q360842","display_name":"SQL/PSM","level":5,"score":0.46959128975868225},{"id":"https://openalex.org/C141589383","wikidata":"https://www.wikidata.org/wiki/Q644775","display_name":"Data Transformation Services","level":5,"score":0.4675033986568451},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.44556888937950134},{"id":"https://openalex.org/C203763787","wikidata":"https://www.wikidata.org/wiki/Q371029","display_name":"Null (SQL)","level":2,"score":0.4426635503768921},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4185056686401367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41506507992744446},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3836877644062042},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.35218480229377747},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2855715751647949},{"id":"https://openalex.org/C164120249","wikidata":"https://www.wikidata.org/wiki/Q995982","display_name":"Web search query","level":3,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1193","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1193","pdf_url":"https://www.aclweb.org/anthology/D18-1193.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1193","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1193","pdf_url":"https://www.aclweb.org/anthology/D18-1193.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2891691255.pdf","grobid_xml":"https://content.openalex.org/works/W2891691255.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W1494362579","https://openalex.org/W1496189301","https://openalex.org/W1522301498","https://openalex.org/W1810532455","https://openalex.org/W1902237438","https://openalex.org/W2096979215","https://openalex.org/W2101964891","https://openalex.org/W2121465811","https://openalex.org/W2126170172","https://openalex.org/W2154268919","https://openalex.org/W2161002933","https://openalex.org/W2163274265","https://openalex.org/W2164155814","https://openalex.org/W2165382777","https://openalex.org/W2189089430","https://openalex.org/W2250225488","https://openalex.org/W2250539671","https://openalex.org/W2250701144","https://openalex.org/W2252123671","https://openalex.org/W2269738476","https://openalex.org/W2626990892","https://openalex.org/W2751448157","https://openalex.org/W2762513422","https://openalex.org/W2768409085","https://openalex.org/W2773790959","https://openalex.org/W2798663534","https://openalex.org/W2798753108","https://openalex.org/W2899771611","https://openalex.org/W2962713807","https://openalex.org/W2962728167","https://openalex.org/W2963357517","https://openalex.org/W2963617989","https://openalex.org/W2963794306","https://openalex.org/W2963847417","https://openalex.org/W2963868320","https://openalex.org/W2963899988","https://openalex.org/W2964121744","https://openalex.org/W2964161178","https://openalex.org/W2964186869","https://openalex.org/W2964271186","https://openalex.org/W4246375690","https://openalex.org/W4255584681","https://openalex.org/W4289494028","https://openalex.org/W4301674784"],"related_works":["https://openalex.org/W151073879","https://openalex.org/W2750425440","https://openalex.org/W2512476881","https://openalex.org/W638381921","https://openalex.org/W3021637214","https://openalex.org/W2240099544","https://openalex.org/W2738342198","https://openalex.org/W2917505743","https://openalex.org/W2791515211","https://openalex.org/W4238156210"],"abstract_inverted_index":{"Most":[0],"existing":[1],"studies":[2],"in":[3,94,127],"text-to-SQL":[4,40,68,142],"tasks":[5],"do":[6],"not":[7],"require":[8],"generating":[9],"complex":[10,37,76,114,141],"SQL":[11,46,52,77,81,115],"queries":[12,78],"with":[13,51,72,148],"multiple":[14,73,80],"clauses":[15,82],"or":[16],"sub-queries,":[17],"and":[18,38,56,75,83,146],"generalizing":[19],"to":[20,34,138],"new,":[21],"unseen":[22,99],"databases.":[23],"In":[24],"this":[25,140],"paper":[26],"we":[27,134],"propose":[28],"SyntaxSQLNet,":[29],"a":[30,45,65,88,109],"syntax":[31,48],"tree":[32],"network":[33],"address":[35],"the":[36,95,121,136,149],"crossdomain":[39],"generation":[41,53],"task.":[42,143],"Syn-taxSQLNet":[43],"employs":[44],"specific":[47],"tree-based":[49],"decoder":[50],"path":[54],"history":[55],"table-aware":[57],"column":[58],"attention":[59],"encoders.":[60],"We":[61,86],"evaluate":[62],"SyntaxSQLNet":[63,106],"on":[64],"new":[66],"large-scale":[67],"corpus":[69],"containing":[70,79],"databases":[71,93],"tables":[74],"nested":[84],"queries.":[85],"use":[87],"database":[89],"split":[90],"setting":[91],"where":[92],"test":[96],"set":[97],"are":[98,135,152],"during":[100],"training.":[101],"Experimental":[102],"results":[103],"show":[104],"that":[105],"can":[107],"handle":[108],"significantly":[110],"greater":[111],"number":[112],"of":[113],"examples":[116],"than":[117],"prior":[118],"work,":[119],"outperforming":[120],"previous":[122],"state-of-the-art":[123],"model":[124],"by":[125],"9.5%":[126],"exact":[128],"matching":[129],"accuracy.":[130],"To":[131],"our":[132],"knowledge,":[133],"first":[137],"study":[139],"Our":[144],"task":[145],"models":[147],"latest":[150],"updates":[151],"available":[153],"at":[154],"https://yale-lily.":[155],"github.io/seq2sql/spider.":[156]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":28},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":38},{"year":2020,"cited_by_count":33},{"year":2019,"cited_by_count":30}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
