{"id":"https://openalex.org/W2951287343","doi":"https://doi.org/10.18653/v1/p19-1370","title":"Learning a Matching Model with Co-teaching for Multi-turn Response Selection in Retrieval-based Dialogue Systems","display_name":"Learning a Matching Model with Co-teaching for Multi-turn Response Selection in Retrieval-based Dialogue Systems","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2951287343","doi":"https://doi.org/10.18653/v1/p19-1370","mag":"2951287343"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1370","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1370","pdf_url":null,"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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/p19-1370","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013569210","display_name":"Jiazhan Feng","orcid":"https://orcid.org/0000-0002-5832-6199"},"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":"Jiazhan Feng","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073065834","display_name":"Chongyang Tao","orcid":"https://orcid.org/0000-0002-4162-2119"},"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":"Chongyang Tao","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101796417","display_name":"Wei Wu","orcid":"https://orcid.org/0000-0001-6572-8471"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wu","raw_affiliation_strings":["Microsoft Corporation, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102220317","display_name":"Yansong Feng","orcid":null},"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":"Yansong Feng","raw_affiliation_strings":["Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037132097","display_name":"Dongyan Zhao","orcid":"https://orcid.org/0000-0002-0396-6703"},"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":"Dongyan Zhao","raw_affiliation_strings":["Center for Data Science, Peking University, Beijing, China","Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100716372","display_name":"Rui Yan","orcid":"https://orcid.org/0000-0002-3356-6823"},"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":"Rui Yan","raw_affiliation_strings":["Center for Data Science, Peking University, Beijing, China","Institute of Computer Science and Technology, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Data Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Computer Science and Technology, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8429,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.93318545,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3805","last_page":"3815"},"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/T12031","display_name":"Speech and dialogue systems","score":0.9994000196456909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8234034776687622},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7619858980178833},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6386081576347351},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.5795110464096069},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.566157877445221},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5555199980735779},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5314810276031494},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.461700975894928},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.44662150740623474},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.41934049129486084},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.41881275177001953},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08516231179237366},{"id":"https://openalex.org/keywords/pedagogy","display_name":"Pedagogy","score":0.06946936249732971}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8234034776687622},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7619858980178833},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6386081576347351},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.5795110464096069},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.566157877445221},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5555199980735779},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5314810276031494},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.461700975894928},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.44662150740623474},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.41934049129486084},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.41881275177001953},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08516231179237366},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.06946936249732971},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1370","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1370","pdf_url":null,"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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1370","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1370","pdf_url":null,"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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W295828404","https://openalex.org/W1522301498","https://openalex.org/W1527783480","https://openalex.org/W1591706642","https://openalex.org/W1975879668","https://openalex.org/W2100913937","https://openalex.org/W2102531443","https://openalex.org/W2128892113","https://openalex.org/W2153579005","https://openalex.org/W2170738476","https://openalex.org/W2256388387","https://openalex.org/W2296073425","https://openalex.org/W2339852062","https://openalex.org/W2418993857","https://openalex.org/W2521114121","https://openalex.org/W2561368124","https://openalex.org/W2767802162","https://openalex.org/W2786471719","https://openalex.org/W2798033004","https://openalex.org/W2798456655","https://openalex.org/W2807880213","https://openalex.org/W2809210859","https://openalex.org/W2885593519","https://openalex.org/W2891416139","https://openalex.org/W2892359699","https://openalex.org/W2908331278","https://openalex.org/W2949446780","https://openalex.org/W2951359136","https://openalex.org/W2962707484","https://openalex.org/W2962768358","https://openalex.org/W2962796276","https://openalex.org/W2962838727","https://openalex.org/W2962854379","https://openalex.org/W2963035145","https://openalex.org/W2963386594","https://openalex.org/W2963780286","https://openalex.org/W2963825865","https://openalex.org/W2963826056","https://openalex.org/W2963962154","https://openalex.org/W2963963856","https://openalex.org/W2963986868","https://openalex.org/W2964092386","https://openalex.org/W2964121744","https://openalex.org/W2964150246","https://openalex.org/W2964309167","https://openalex.org/W2964352131","https://openalex.org/W4294170691","https://openalex.org/W4300125564"],"related_works":["https://openalex.org/W623607250","https://openalex.org/W4245429118","https://openalex.org/W4245505501","https://openalex.org/W2921334381","https://openalex.org/W4255529442","https://openalex.org/W4212927854","https://openalex.org/W1545246811","https://openalex.org/W4236448199","https://openalex.org/W4383877548","https://openalex.org/W4232403550"],"abstract_inverted_index":{"We":[0],"study":[1],"learning":[2,145],"of":[3,23,154],"a":[4,24,35,45,118,121],"matching":[5,37,73,156],"model":[6,38,83,107],"for":[7],"response":[8],"selection":[9],"in":[10,30,113],"retrieval-based":[11],"dialogue":[12],"systems.":[13],"The":[14],"problem":[15],"is":[16,27],"equally":[17],"important":[18],"with":[19,49,58,63,75],"designing":[20],"the":[21,67,85,93,98,102,105,123,143,152],"architecture":[22],"model,":[25,95],"but":[26],"less":[28],"explored":[29],"existing":[31,155],"literature.":[32],"To":[33],"learn":[34,71,126],"robust":[36],"from":[39,88,104,127],"noisy":[40],"training":[41,77,90],"data,":[42],"we":[43,69],"propose":[44],"general":[46],"co-teaching":[47],"framework":[48],"three":[50],"specific":[51],"teaching":[52,57,62],"strategies":[53],"that":[54,142],"cover":[55],"both":[56,117],"loss":[59],"functions":[60],"and":[61,96,120,130,149],"data":[64,139],"curriculum.":[65],"Under":[66],"framework,":[68],"simultaneously":[70],"two":[72,124,137],"models":[74,125],"independent":[76],"sets.":[78],"In":[79],"each":[80,128],"iteration,":[81],"one":[82],"transfers":[84],"knowledge":[86],"learned":[87],"its":[89],"set":[91],"to":[92,110],"other":[94,106,129],"at":[97],"same":[99],"time":[100],"receives":[101],"guide":[103],"on":[108,136],"how":[109],"overcome":[111],"noise":[112],"training.":[114],"Through":[115],"being":[116],"teacher":[119],"student,":[122],"get":[131],"improved":[132],"together.":[133],"Evaluation":[134],"results":[135],"public":[138],"sets":[140],"indicate":[141],"proposed":[144],"approach":[146],"can":[147],"generally":[148],"significantly":[150],"improve":[151],"performance":[153],"models.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":12}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}