{"id":"https://openalex.org/W2953071719","doi":"https://doi.org/10.18653/v1/p19-1360","title":"Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention","display_name":"Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2953071719","doi":"https://doi.org/10.18653/v1/p19-1360","mag":"2953071719"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1360","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1360","pdf_url":"https://www.aclweb.org/anthology/P19-1360.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1360.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103103242","display_name":"Wenhu Chen","orcid":"https://orcid.org/0000-0002-8609-7821"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wenhu Chen","raw_affiliation_strings":["University of California, Santa Barbara, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088339142","display_name":"Jianshu Chen","orcid":"https://orcid.org/0000-0001-8216-2756"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianshu Chen","raw_affiliation_strings":["Tencent AI Lab, Bellevue, WA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034095320","display_name":"Pengda Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengda Qin","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047709762","display_name":"Xifeng Yan","orcid":"https://orcid.org/0009-0000-6508-4792"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xifeng Yan","raw_affiliation_strings":["University of California, Santa Barbara, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100702488","display_name":"William Yang Wang","orcid":"https://orcid.org/0000-0002-0878-1257"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Yang Wang","raw_affiliation_strings":["University of California, Santa Barbara, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Santa Barbara, CA, USA","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103103242"],"corresponding_institution_ids":["https://openalex.org/I154570441"],"apc_list":null,"apc_paid":null,"fwci":14.90092132,"has_fulltext":true,"cited_by_count":129,"citation_normalized_percentile":{"value":0.99048151,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3696","last_page":"3709"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9969000220298767,"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"}},{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","score":0.9943000078201294,"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/dialog-box","display_name":"Dialog box","score":0.8450629711151123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.827124297618866},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7382710576057434},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6649141907691956},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6021322011947632},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5864242911338806},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4371602535247803},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3801374137401581},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.06184959411621094},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.06119072437286377}],"concepts":[{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.8450629711151123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.827124297618866},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7382710576057434},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6649141907691956},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6021322011947632},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5864242911338806},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4371602535247803},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3801374137401581},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.06184959411621094},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.06119072437286377},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1360","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1360","pdf_url":"https://www.aclweb.org/anthology/P19-1360.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1360","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1360","pdf_url":"https://www.aclweb.org/anthology/P19-1360.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 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320316083","display_name":"Tencent","ror":"https://ror.org/00hhjss72"},{"id":"https://openalex.org/F4320320273","display_name":"University of Cambridge","ror":"https://ror.org/013meh722"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2953071719.pdf","grobid_xml":"https://content.openalex.org/works/W2953071719.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1948566616","https://openalex.org/W1975244201","https://openalex.org/W2101105183","https://openalex.org/W2251235149","https://openalex.org/W2291723583","https://openalex.org/W2468710617","https://openalex.org/W2470040910","https://openalex.org/W2518570122","https://openalex.org/W2620558438","https://openalex.org/W2798914047","https://openalex.org/W2803392141","https://openalex.org/W2804010326","https://openalex.org/W2896457183","https://openalex.org/W2949252816","https://openalex.org/W2962738716","https://openalex.org/W2962788148","https://openalex.org/W2963134326","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963412005","https://openalex.org/W2963491014","https://openalex.org/W2963797754","https://openalex.org/W2964006684","https://openalex.org/W2964101860","https://openalex.org/W2964121744","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W2098987383","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W2417260800","https://openalex.org/W2795961259","https://openalex.org/W1596203174","https://openalex.org/W2117933979","https://openalex.org/W1590307681","https://openalex.org/W4312814274"],"abstract_inverted_index":{"Semantically":[0],"controlled":[1],"neural":[2,117],"response":[3,118],"generation":[4],"on":[5,63,93,135],"limited-domain":[6],"has":[7],"achieved":[8],"great":[9],"performance.":[10],"However,":[11],"moving":[12],"towards":[13],"multi-domain":[14],"large-scale":[15,122],"scenarios":[16],"are":[17],"shown":[18],"to":[19,48,77,89,114],"be":[20,112],"difficult":[21],"because":[22],"the":[23,32,43,64,94,116,121,133],"possible":[24],"combinations":[25],"of":[26,34,45],"semantic":[27],"inputs":[28],"grow":[29],"exponentially":[30],"with":[31],"number":[33],"domains.":[35],"To":[36],"alleviate":[37],"such":[38,69],"scalability":[39],"issue,":[40],"we":[41,67,85],"exploit":[42],"structure":[44,71],"dialog":[46,95,108],"acts":[47],"build":[49,78],"a":[50,60,79,129],"multi-layer":[51],"hierarchical":[52,80],"graph,":[53],"where":[54,84],"each":[55,104],"act":[56,96,109],"is":[57],"represented":[58],"as":[59,73],"root-to-leaf":[61],"route":[62],"graph.":[65,97],"Then,":[66],"incorporate":[68],"graph":[70],"prior":[72],"an":[74],"inductive":[75],"bias":[76],"disentangled":[81],"self-attention":[82],"network,":[83],"disentangle":[86],"attention":[87],"heads":[88,102],"model":[90,126],"designated":[91],"nodes":[92],"By":[98],"activating":[99],"different":[100],"(disentangled)":[101],"at":[103],"layer,":[105],"combinatorially":[106],"many":[107],"semantics":[110],"can":[111,127],"modeled":[113],"control":[115],"generation.":[119],"On":[120],"Multi-Domain-WOZ":[123],"dataset,":[124],"our":[125],"yield":[128],"significant":[130],"improvement":[131],"over":[132],"baselines":[134],"various":[136],"automatic":[137],"and":[138],"human":[139],"evaluation":[140],"metrics.":[141]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":24},{"year":2020,"cited_by_count":46},{"year":2019,"cited_by_count":3}],"updated_date":"2026-02-13T15:27:49.765798","created_date":"2025-10-10T00:00:00"}