{"id":"https://openalex.org/W3034975599","doi":"https://doi.org/10.1145/3397271.3401255","title":"Improving Contextual Language Models for Response Retrieval in Multi-Turn Conversation","display_name":"Improving Contextual Language Models for Response Retrieval in Multi-Turn Conversation","publication_year":2020,"publication_date":"2020-07-25","ids":{"openalex":"https://openalex.org/W3034975599","doi":"https://doi.org/10.1145/3397271.3401255","mag":"3034975599"},"language":"en","primary_location":{"id":"doi:10.1145/3397271.3401255","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101511390","display_name":"Junyu Lu","orcid":"https://orcid.org/0000-0002-4094-2540"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junyu Lu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025992629","display_name":"Xiancong Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiancong Ren","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055826974","display_name":"Yazhou Ren","orcid":"https://orcid.org/0000-0001-7705-4603"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yazhou Ren","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346418","display_name":"Ao Liu","orcid":"https://orcid.org/0000-0002-8412-6414"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ao Liu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051227924","display_name":"Zenglin Xu","orcid":"https://orcid.org/0000-0001-5550-6461"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zenglin Xu","raw_affiliation_strings":["Harbin Institute of Technology, Peng Cheng Lab, & University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Peng Cheng Lab, & University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I4210136793","https://openalex.org/I204983213","https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101511390"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":4.3745,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.95285711,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1805","last_page":"1808"},"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/T12031","display_name":"Speech and dialogue systems","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9987000226974487,"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":0.8629024028778076},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.7433465719223022},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6935611367225647},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6809627413749695},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.6384400129318237},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6051924228668213},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5591523051261902},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.5447791814804077},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5407955050468445},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.45717838406562805},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.45389673113822937},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42712461948394775},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3531810939311981},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.09912580251693726}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8629024028778076},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7433465719223022},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6935611367225647},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6809627413749695},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.6384400129318237},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6051924228668213},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5591523051261902},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.5447791814804077},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5407955050468445},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.45717838406562805},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.45389673113822937},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42712461948394775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3531810939311981},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.09912580251693726},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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":1,"locations":[{"id":"doi:10.1145/3397271.3401255","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3397271.3401255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6700000166893005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2014415866","https://openalex.org/W2339852062","https://openalex.org/W2739634080","https://openalex.org/W2798456655","https://openalex.org/W2822830299","https://openalex.org/W2891416139","https://openalex.org/W2908331278","https://openalex.org/W2951287343","https://openalex.org/W2952285288","https://openalex.org/W2952813980","https://openalex.org/W2962854379","https://openalex.org/W2963341956","https://openalex.org/W2965373594","https://openalex.org/W2970648534","https://openalex.org/W2971190479","https://openalex.org/W2987002320","https://openalex.org/W3210120707"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W1968552888","https://openalex.org/W2374116601","https://openalex.org/W3093134843","https://openalex.org/W1511346092","https://openalex.org/W3133700904","https://openalex.org/W4288267738","https://openalex.org/W2964413124","https://openalex.org/W4388937922","https://openalex.org/W3113264705"],"abstract_inverted_index":{"As":[0],"an":[1],"important":[2],"branch":[3],"of":[4,34],"current":[5],"dialogue":[6,53,114],"systems,":[7],"retrieval-based":[8],"chatbots":[9],"leverage":[10],"information":[11],"retrieval":[12],"to":[13,47,65,69,90,110],"select":[14],"proper":[15],"predefined":[16],"responses.":[17],"Various":[18],"promising":[19],"architectures":[20],"have":[21],"been":[22],"designed":[23,64],"for":[24,116],"boosting":[25],"response":[26,54],"retrieval,":[27],"however,":[28],"few":[29],"researches":[30],"exploit":[31],"the":[32,35,59,77,92],"effectiveness":[33],"pre-trained":[36],"contextual":[37,49,105,113],"language":[38,50,106],"models.":[39,136],"In":[40,57],"this":[41],"paper,":[42],"we":[43,75],"propose":[44,76],"two":[45],"approaches":[46,130],"adapt":[48],"models":[51,107],"in":[52],"selection":[55],"task.":[56],"detail,":[58],"Speaker":[60],"Segmentation":[61],"approach":[62],"is":[63],"discriminate":[66],"different":[67,87],"speakers":[68],"fully":[70],"utilize":[71],"speaker":[72],"characteristics.":[73],"Besides,":[74],"Dialogue":[78],"Augmentation":[79],"approach,":[80],"i.e.,":[81],"cutting":[82],"off":[83],"real":[84],"conversations":[85],"at":[86],"time":[88],"points,":[89],"enlarge":[91],"training":[93],"corpora.":[94],"Compared":[95],"with":[96],"previous":[97],"works":[98],"which":[99],"use":[100],"utterance-level":[101],"representations,":[102],"our":[103,128],"augmented":[104],"are":[108],"able":[109],"obtain":[111],"top-hole":[112],"representations":[115],"deeper":[117],"semantic":[118],"understanding.":[119],"Evaluation":[120],"on":[121],"three":[122],"large-scale":[123],"datasets":[124],"has":[125],"demonstrated":[126],"that":[127],"proposed":[129],"yield":[131],"better":[132],"performance":[133],"than":[134],"existing":[135]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":15}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}