{"id":"https://openalex.org/W2807880213","doi":"https://doi.org/10.24963/ijcai.2018/614","title":"Get The Point of My Utterance! Learning Towards Effective Responses with Multi-Head Attention Mechanism","display_name":"Get The Point of My Utterance! Learning Towards Effective Responses with Multi-Head Attention Mechanism","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2807880213","doi":"https://doi.org/10.24963/ijcai.2018/614","mag":"2807880213"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/614","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/614","pdf_url":"https://www.ijcai.org/proceedings/2018/0614.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0614.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","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/A5021862101","display_name":"Shen Gao","orcid":"https://orcid.org/0000-0003-1301-3700"},"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":"Shen Gao","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/A5052835344","display_name":"Mingyue Shang","orcid":"https://orcid.org/0009-0000-6523-3516"},"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":"Mingyue Shang","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/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"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyan Zhao","raw_affiliation_strings":["Beijing Institute of Big Data Research, Beijing, China","Institute of Computer Science and Technology, , Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Big Data Research, Beijing, China","institution_ids":["https://openalex.org/I4210096250"]},{"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"]},{"id":"https://openalex.org/I4210096250","display_name":"Beijing Institute of Big Data Research","ror":"https://ror.org/00s1sz824","country_code":"CN","type":"facility","lineage":["https://openalex.org/I20231570","https://openalex.org/I37796252","https://openalex.org/I4210096250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yan","raw_affiliation_strings":["Beijing Institute of Big Data Research, Beijing, China","Institute of Computer Science and Technology, , Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Big Data Research, Beijing, China","institution_ids":["https://openalex.org/I4210096250"]},{"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":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":171,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4418","last_page":"4424"},"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":0.9987999796867371,"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":0.9986000061035156,"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/utterance","display_name":"Utterance","score":0.8891295194625854},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8380154371261597},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.7295861840248108},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.7020321488380432},{"id":"https://openalex.org/keywords/dialog-box","display_name":"Dialog box","score":0.695618748664856},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6575250625610352},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6004388928413391},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5946956276893616},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.58331298828125},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.47244197130203247},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.42508867383003235},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38458818197250366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.335331529378891}],"concepts":[{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.8891295194625854},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8380154371261597},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.7295861840248108},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.7020321488380432},{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.695618748664856},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6575250625610352},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6004388928413391},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5946956276893616},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.58331298828125},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.47244197130203247},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.42508867383003235},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38458818197250366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.335331529378891},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2018/614","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/614","pdf_url":"https://www.ijcai.org/proceedings/2018/0614.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/614","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/614","pdf_url":"https://www.ijcai.org/proceedings/2018/0614.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G2602370256","display_name":null,"funder_award_id":"2017YFC0804001","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8874090203","display_name":"\u57fa\u4e8e\u5927\u89c4\u6a21\u77e5\u8bc6\u5e93\u7684\u95ee\u7b54\u7cfb\u7edf\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61672058","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2807880213.pdf","grobid_xml":"https://content.openalex.org/works/W2807880213.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1552182777","https://openalex.org/W1924770834","https://openalex.org/W2064675550","https://openalex.org/W2101105183","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2146502635","https://openalex.org/W2328886022","https://openalex.org/W2521114121","https://openalex.org/W2538399326","https://openalex.org/W2557436004","https://openalex.org/W2584220694","https://openalex.org/W2597655663","https://openalex.org/W2604444020","https://openalex.org/W2741363662","https://openalex.org/W2756487349","https://openalex.org/W2757121784","https://openalex.org/W2953127297","https://openalex.org/W2962717182","https://openalex.org/W2962965405","https://openalex.org/W2963206148","https://openalex.org/W2963790827","https://openalex.org/W2963903950","https://openalex.org/W2963963856","https://openalex.org/W2963986868","https://openalex.org/W2964178377","https://openalex.org/W2964199361","https://openalex.org/W2964308564","https://openalex.org/W3022187094","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2063157598","https://openalex.org/W2107559347","https://openalex.org/W2013809956","https://openalex.org/W2097043665","https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424"],"abstract_inverted_index":{"Attention":[0,52],"mechanism":[1,87],"has":[2],"become":[3],"a":[4,49,71],"popular":[5],"and":[6,25,93],"widely":[7],"used":[8],"component":[9],"in":[10,44],"sequence-to-sequence":[11],"models.":[12],"However,":[13],"previous":[14],"research":[15],"on":[16,82],"neural":[17],"generative":[18,56],"dialogue":[19],"systems":[20],"always":[21,33],"generates":[22],"universal":[23],"responses,":[24],"the":[26,31,36,67],"attention":[27,78],"distribution":[28],"learned":[29],"by":[30],"model":[32,103],"attends":[34],"to":[35,75,80,89],"same":[37],"semantic":[38,64],"aspect.":[39],"To":[40],"solve":[41],"this":[42,45],"problem,":[43],"paper,":[46],"we":[47],"propose":[48],"novel":[50],"Multi-Head":[51],"Mechanism":[53],"(MHAM)":[54],"for":[55],"dialog":[57],"systems,":[58],"which":[59],"aims":[60],"at":[61],"capturing":[62],"multiple":[63],"aspects":[65],"from":[66],"user":[68],"utterance.":[69],"Further,":[70],"regularizer":[72],"is":[73],"formulated":[74],"force":[76],"different":[77],"heads":[79],"concentrate":[81],"certain":[83],"aspects.":[84],"The":[85],"proposed":[86,102],"leads":[88],"more":[90],"informative,":[91],"diverse,":[92],"relevant":[94],"response":[95],"generated.":[96],"Experimental":[97],"results":[98],"show":[99],"that":[100],"our":[101],"outperforms":[104],"several":[105],"strong":[106],"baselines.":[107]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":37},{"year":2019,"cited_by_count":31},{"year":2018,"cited_by_count":9}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
