{"id":"https://openalex.org/W4303939410","doi":"https://doi.org/10.48550/arxiv.2204.12186","title":"Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Loss","display_name":"Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Loss","publication_year":2022,"publication_date":"2022-04-26","ids":{"openalex":"https://openalex.org/W4303939410","doi":"https://doi.org/10.48550/arxiv.2204.12186"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2204.12186","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.12186","pdf_url":"https://arxiv.org/pdf/2204.12186","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2204.12186","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116592777","display_name":"Kun Wu","orcid":"https://orcid.org/0000-0003-2095-2140"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wu, Kun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651061","display_name":"Lijie Wang","orcid":"https://orcid.org/0000-0003-1702-0422"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lijie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100647402","display_name":"Zhenghua Li","orcid":"https://orcid.org/0000-0002-3911-801X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Zhenghua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5112673776","display_name":"Xinyan Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Xinyan","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5116592777"],"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":0.9997000098228455,"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":0.9997000098228455,"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":0.9922999739646912,"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":0.9634000062942505,"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":0.8592429161071777},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.6782451868057251},{"id":"https://openalex.org/keywords/top-down-parsing","display_name":"Top-down parsing","score":0.6220352053642273},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5558013916015625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.518314003944397},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.500288724899292},{"id":"https://openalex.org/keywords/parser-combinator","display_name":"Parser combinator","score":0.48742106556892395},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4801208972930908},{"id":"https://openalex.org/keywords/sql","display_name":"SQL","score":0.47872066497802734},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4429633319377899},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.4402520954608917},{"id":"https://openalex.org/keywords/parsing-expression-grammar","display_name":"Parsing expression grammar","score":0.4206102788448334},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2388155162334442},{"id":"https://openalex.org/keywords/context-free-grammar","display_name":"Context-free grammar","score":0.15418225526809692},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1163521409034729},{"id":"https://openalex.org/keywords/l-attributed-grammar","display_name":"L-attributed grammar","score":0.11564218997955322}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8592429161071777},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6782451868057251},{"id":"https://openalex.org/C42560504","wikidata":"https://www.wikidata.org/wiki/Q15419395","display_name":"Top-down parsing","level":3,"score":0.6220352053642273},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5558013916015625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.518314003944397},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.500288724899292},{"id":"https://openalex.org/C118364021","wikidata":"https://www.wikidata.org/wiki/Q7139956","display_name":"Parser combinator","level":3,"score":0.48742106556892395},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4801208972930908},{"id":"https://openalex.org/C510870499","wikidata":"https://www.wikidata.org/wiki/Q47607","display_name":"SQL","level":2,"score":0.47872066497802734},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4429633319377899},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.4402520954608917},{"id":"https://openalex.org/C146810361","wikidata":"https://www.wikidata.org/wiki/Q32271","display_name":"Parsing expression grammar","level":5,"score":0.4206102788448334},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2388155162334442},{"id":"https://openalex.org/C97212296","wikidata":"https://www.wikidata.org/wiki/Q338047","display_name":"Context-free grammar","level":3,"score":0.15418225526809692},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1163521409034729},{"id":"https://openalex.org/C67621940","wikidata":"https://www.wikidata.org/wiki/Q3113340","display_name":"L-attributed grammar","level":4,"score":0.11564218997955322},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2204.12186","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.12186","pdf_url":"https://arxiv.org/pdf/2204.12186","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2204.12186","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2204.12186","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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2204.12186","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.12186","pdf_url":"https://arxiv.org/pdf/2204.12186","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.49000000953674316,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3143982968","https://openalex.org/W4320024782","https://openalex.org/W2804916787","https://openalex.org/W2529664582","https://openalex.org/W1574037173","https://openalex.org/W1929722976","https://openalex.org/W2077094028","https://openalex.org/W2383537280","https://openalex.org/W2014558227","https://openalex.org/W2389755172"],"abstract_inverted_index":{"Grammar-based":[0],"parsers":[1,78],"have":[2],"achieved":[3],"high":[4],"performance":[5],"in":[6,33,87],"the":[7,20],"cross-domain":[8],"text-to-SQL":[9],"parsing":[10,52],"task,":[11],"but":[12],"suffer":[13],"from":[14],"low":[15],"decoding":[16,60,90],"efficiency":[17],"due":[18],"to":[19,38,64],"much":[21],"larger":[22],"number":[23],"of":[24,31,76],"actions":[25],"for":[26,51],"grammar":[27],"selection":[28],"than":[29],"that":[30,80],"tokens":[32],"SQL":[34,41],"queries.":[35],"Meanwhile,":[36],"how":[37],"better":[39],"align":[40],"clauses":[42],"and":[43,61,72,89],"question":[44],"segments":[45],"has":[46],"been":[47],"a":[48],"key":[49],"challenge":[50],"performance.":[53],"Therefore,":[54],"this":[55],"paper":[56],"proposes":[57],"clause-level":[58],"parallel":[59],"alignment":[62],"loss":[63],"enhance":[65],"two":[66,77],"high-performance":[67],"grammar-based":[68],"parsers,":[69],"i.e.,":[70],"RATSQL":[71],"LGESQL.":[73],"Experimental":[74],"results":[75],"show":[79],"our":[81],"method":[82],"obtains":[83],"consistent":[84],"improvements":[85],"both":[86],"accuracy":[88],"speed.":[91]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}