{"id":"https://openalex.org/W4416035880","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.36","title":"RACQC: Advanced Retrieval-Augmented Generation for Chinese Query Correction","display_name":"RACQC: Advanced Retrieval-Augmented Generation for Chinese Query Correction","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416035880","doi":"https://doi.org/10.18653/v1/2025.findings-emnlp.36"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.36","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.36","pdf_url":"https://aclanthology.org/2025.findings-emnlp.36.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-emnlp.36.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007644743","display_name":"Jin Bo Su","orcid":"https://orcid.org/0000-0002-1823-8928"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinbo Su","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062517991","display_name":"Ling Gao","orcid":"https://orcid.org/0000-0001-7320-1442"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lingzhe Gao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100776276","display_name":"Li Wei","orcid":"https://orcid.org/0000-0002-3735-588X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033422038","display_name":"S. B. Liu","orcid":"https://orcid.org/0000-0001-8787-930X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shihao Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104687373","display_name":"Haojie Lei","orcid":"https://orcid.org/0009-0002-9160-8670"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haojie Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Xinyi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xinyi Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077070675","display_name":"Yuanzhao Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuanzhao Guo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015690128","display_name":"Ke Wang","orcid":"https://orcid.org/0000-0003-2982-4153"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ke Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008762356","display_name":"Daiting Shi","orcid":"https://orcid.org/0000-0003-4926-3357"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daiting Shi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101771060","display_name":"Dawei Yin","orcid":"https://orcid.org/0000-0002-0684-6205"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dawei Yin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43302554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"675","last_page":"689"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.40059998631477356,"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"}},"topics":[{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.40059998631477356,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.121799997985363,"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"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.09149999916553497,"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/feature","display_name":"Feature (linguistics)","score":0.28519999980926514},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.2752000093460083},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.23190000653266907},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.23090000450611115}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6495000123977661},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3889999985694885},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.30660000443458557},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2694000005722046},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.25920000672340393},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.23190000653266907},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.23090000450611115},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2222999930381775}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-emnlp.36","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.36","pdf_url":"https://aclanthology.org/2025.findings-emnlp.36.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-emnlp.36","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-emnlp.36","pdf_url":"https://aclanthology.org/2025.findings-emnlp.36.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":"Findings of the Association for Computational Linguistics: EMNLP 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416035880.pdf","grobid_xml":"https://content.openalex.org/works/W4416035880.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"web":[1],"search":[2,155],"scenarios,":[3],"erroneous":[4],"queries":[5],"frequently":[6],"degrade":[7],"users'":[8],"experience":[9],"through":[10,91],"irrelevant":[11],"results,":[12],"underscoring":[13],"the":[14,38,127,154,161,165],"pivotal":[15],"role":[16],"of":[17,151],"Chinese":[18,74,121],"Spelling":[19],"Check":[20],"(CSC)":[21],"systems.Although":[22],"large":[23],"language":[24],"models":[25],"(LLMs)":[26],"exhibit":[27],"remarkable":[28],"capabilities":[29],"across":[30],"many":[31],"tasks,":[32],"they":[33],"face":[34],"critical":[35],"challenges":[36],"in":[37,47,64,143],"CSC":[39,144],"scenario:":[40],"(1)":[41,86],"poor":[42],"generalization":[43],"to":[44,53,55,60,94,111,125],"rare":[45,96],"entities":[46,97],"open-domain":[48],"searches,":[49],"and":[50,81,98,105,158],"(2)":[51,106],"failure":[52],"adapt":[54],"temporal":[56],"entity":[57,129],"variations":[58],"due":[59],"static":[61],"parameters,":[62],"resulting":[63],"serious":[65],"overcorrection":[66],"issues.To":[67],"tackle":[68],"this,":[69],"we":[70,116],"present":[71],"RACQC,":[72],"a":[73,119,148],"Query":[75,122],"Correction":[76,123],"system":[77],"with":[78],"Retrieval-Augmented":[79],"Generation(RAG)":[80],"multi-task":[82],"learning.Specifically,":[83],"our":[84],"approach":[85],"integrates":[87],"dynamic":[88],"knowledge":[89],"retrieval":[90],"entity-centric":[92],"RAG":[93],"address":[95],"innovatively":[99],"proposes":[100],"an":[101],"entity-title":[102],"collaborative":[103],"corpus,":[104],"employs":[107],"contrastive":[108],"correction":[109,130],"tasks":[110],"mitigate":[112],"LLM":[113],"over-correction":[114],"tendencies.Furthermore,":[115],"propose":[117],"MDCQC,":[118],"Multi-Domain":[120],"benchmark":[124,157],"test":[126],"model's":[128],"capabilities.Extensive":[131],"experiments":[132],"on":[133,153,160],"several":[134],"datasets":[135],"show":[136],"that":[137],"RACQC":[138,146],"significantly":[139],"outperforms":[140],"existing":[141],"baselines":[142],"tasks.Specifically,":[145],"achieves":[147],"maximum":[149],"improvement":[150],"+9.92%":[152],"scenario":[156],"+3.2%":[159],"general-domain":[162],"dataset":[163],"under":[164],"F":[166],"1":[167],"metric.":[168]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-08T00:00:00"}