{"id":"https://openalex.org/W2740747242","doi":"https://doi.org/10.18653/v1/p17-1018","title":"Gated Self-Matching Networks for Reading Comprehension and Question Answering","display_name":"Gated Self-Matching Networks for Reading Comprehension and Question Answering","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2740747242","doi":"https://doi.org/10.18653/v1/p17-1018","mag":"2740747242"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p17-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1018","pdf_url":"https://www.aclweb.org/anthology/P17-1018.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 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P17-1018.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100370076","display_name":"Wenhui Wang","orcid":"https://orcid.org/0000-0002-5884-6098"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhui Wang","raw_affiliation_strings":["Key Laboratory of Computational Linguistics, Peking University, MOE, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Linguistics, Peking University, MOE, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072808499","display_name":"Nan Yang","orcid":"https://orcid.org/0000-0002-2621-8927"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]},{"id":"https://openalex.org/I4210157323","display_name":"South China Institute of Collaborative Innovation","ror":"https://ror.org/04jnpk588","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210157323","https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Yang","raw_affiliation_strings":["Collaborative Innovation Center for Language Ability, Xuzhou, 221009, China","Microsoft Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center for Language Ability, Xuzhou, 221009, China","institution_ids":["https://openalex.org/I4210157323"]},{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014662947","display_name":"Furu Wei","orcid":"https://orcid.org/0000-0002-7810-5852"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]},{"id":"https://openalex.org/I4210157323","display_name":"South China Institute of Collaborative Innovation","ror":"https://ror.org/04jnpk588","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210157323","https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Furu Wei","raw_affiliation_strings":["Collaborative Innovation Center for Language Ability, Xuzhou, 221009, China","Microsoft Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center for Language Ability, Xuzhou, 221009, China","institution_ids":["https://openalex.org/I4210157323"]},{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021459300","display_name":"Baobao Chang","orcid":"https://orcid.org/0000-0003-2824-6750"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baobao Chang","raw_affiliation_strings":["Key Laboratory of Computational Linguistics, Peking University, MOE, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Linguistics, Peking University, MOE, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100701572","display_name":"Ming Zhou","orcid":"https://orcid.org/0000-0002-2551-2964"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]},{"id":"https://openalex.org/I4210157323","display_name":"South China Institute of Collaborative Innovation","ror":"https://ror.org/04jnpk588","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210157323","https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Zhou","raw_affiliation_strings":["Collaborative Innovation Center for Language Ability, Xuzhou, 221009, China","Microsoft Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Collaborative Innovation Center for Language Ability, Xuzhou, 221009, China","institution_ids":["https://openalex.org/I4210157323"]},{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100701572"],"corresponding_institution_ids":["https://openalex.org/I4210113369","https://openalex.org/I4210157323"],"apc_list":null,"apc_paid":null,"fwci":67.6897,"has_fulltext":true,"cited_by_count":721,"citation_normalized_percentile":{"value":0.99917812,"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":"189","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9990000128746033,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9914000034332275,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8270420432090759},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.8104705810546875},{"id":"https://openalex.org/keywords/pointer","display_name":"Pointer (user interface)","score":0.7444803714752197},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6620387434959412},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5992385149002075},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.5591318607330322},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5077961087226868},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5042005777359009},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4296233355998993},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.4242391288280487},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.4217715859413147},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08321031928062439},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07841211557388306}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8270420432090759},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.8104705810546875},{"id":"https://openalex.org/C150202949","wikidata":"https://www.wikidata.org/wiki/Q107602","display_name":"Pointer (user interface)","level":2,"score":0.7444803714752197},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6620387434959412},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5992385149002075},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.5591318607330322},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5077961087226868},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5042005777359009},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4296233355998993},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.4242391288280487},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.4217715859413147},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08321031928062439},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07841211557388306},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p17-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1018","pdf_url":"https://www.aclweb.org/anthology/P17-1018.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 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p17-1018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1018","pdf_url":"https://www.aclweb.org/anthology/P17-1018.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 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4896575247","display_name":null,"funder_award_id":"2014CB340504","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2740747242.pdf","grobid_xml":"https://content.openalex.org/works/W2740747242.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W179875071","https://openalex.org/W1544827683","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2118463056","https://openalex.org/W2123442489","https://openalex.org/W2125436846","https://openalex.org/W2126209950","https://openalex.org/W2133564696","https://openalex.org/W2157331557","https://openalex.org/W2250539671","https://openalex.org/W2251818205","https://openalex.org/W2251830157","https://openalex.org/W2252016937","https://openalex.org/W2267186426","https://openalex.org/W2413794162","https://openalex.org/W2415755012","https://openalex.org/W2416043263","https://openalex.org/W2417356443","https://openalex.org/W2507756961","https://openalex.org/W2516930406","https://openalex.org/W2521709538","https://openalex.org/W2541604458","https://openalex.org/W2551396370","https://openalex.org/W2552027021","https://openalex.org/W2556691798","https://openalex.org/W2558203065","https://openalex.org/W2566011400","https://openalex.org/W2600024417","https://openalex.org/W2601454101","https://openalex.org/W2750557179","https://openalex.org/W2949615363","https://openalex.org/W2951534261","https://openalex.org/W2962809918","https://openalex.org/W2962958286","https://openalex.org/W2963019137","https://openalex.org/W2963344337","https://openalex.org/W2963542836","https://openalex.org/W2963595025","https://openalex.org/W2963748441","https://openalex.org/W2963871484","https://openalex.org/W2964185324","https://openalex.org/W2964267515","https://openalex.org/W3104486441","https://openalex.org/W4394665226"],"related_works":["https://openalex.org/W2384605597","https://openalex.org/W2387743295","https://openalex.org/W2115758952","https://openalex.org/W3082787378","https://openalex.org/W2136007095","https://openalex.org/W2366230879","https://openalex.org/W2082296339","https://openalex.org/W2030403248","https://openalex.org/W2161828220","https://openalex.org/W1972348076"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2,124],"we":[3,43],"present":[4],"the":[5,27,38,51,55,64,70,75,80,87,96,103,108,113,118,123,128,132],"gated":[6,32],"selfmatching":[7],"networks":[8,35,72],"for":[9,135],"reading":[10],"comprehension":[11],"style":[12],"question":[13,28],"answering,":[14],"which":[15,59],"aims":[16],"to":[17,36,49,73,115],"answer":[18],"questions":[19],"from":[20,63,79],"a":[21,45],"given":[22],"passage.":[23,66],"We":[24,67,82],"first":[25,129],"match":[26,101],"and":[29,138],"passage":[30,40,56],"with":[31],"attention-based":[33],"recurrent":[34],"obtain":[37],"question-aware":[39],"representation.":[41],"Then":[42],"propose":[44],"self-matching":[46],"attention":[47],"mechanism":[48],"refine":[50],"representation":[52],"by":[53],"matching":[54],"against":[57],"itself,":[58],"effectively":[60],"encodes":[61],"information":[62],"whole":[65],"finally":[68],"employ":[69],"pointer":[71],"locate":[74],"positions":[76],"of":[77,99,120,122],"answers":[78],"passages.":[81],"conduct":[83],"extensive":[84],"experiments":[85],"on":[86,95,102,131],"SQuAD":[88,133],"dataset.":[89],"The":[90],"single":[91,137],"model":[92,110,126],"achieves":[93],"71.3%":[94],"evaluation":[97],"metrics":[98],"exact":[100],"hidden":[104],"test":[105],"set,":[106],"while":[107],"ensemble":[109,139],"further":[111],"boosts":[112],"results":[114],"75.9%.":[116],"At":[117],"time":[119],"submission":[121],"our":[125],"holds":[127],"place":[130],"leaderboard":[134],"both":[136],"model.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":41},{"year":2022,"cited_by_count":64},{"year":2021,"cited_by_count":100},{"year":2020,"cited_by_count":144},{"year":2019,"cited_by_count":179},{"year":2018,"cited_by_count":142},{"year":2017,"cited_by_count":24}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
