{"id":"https://openalex.org/W2962717182","doi":"https://doi.org/10.18653/v1/p17-1061","title":"Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders","display_name":"Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2962717182","doi":"https://doi.org/10.18653/v1/p17-1061","mag":"2962717182"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p17-1061","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1061","pdf_url":"https://www.aclweb.org/anthology/P17-1061.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\n          Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P17-1061.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114246802","display_name":"Tiancheng Zhao","orcid":"https://orcid.org/0000-0002-7443-0666"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tiancheng Zhao","raw_affiliation_strings":["Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100626034","display_name":"Ran Zhao","orcid":"https://orcid.org/0000-0002-8224-2091"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ran Zhao","raw_affiliation_strings":["Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077285164","display_name":"Maxine Esk\u00e9nazi","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Maxine Eskenazi","raw_affiliation_strings":["Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Language Technologies Institute Carnegie Mellon University Pittsburgh, Pennsylvania, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100626034","https://openalex.org/A5114246802"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":77.8592,"has_fulltext":true,"cited_by_count":711,"citation_normalized_percentile":{"value":0.99920576,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"654","last_page":"664"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T12031","display_name":"Speech and dialogue systems","score":0.9983999729156494,"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":0.7797583341598511},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7408198118209839},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5856115221977234},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5396734476089478},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4905380606651306},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4472436308860779},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42083853483200073},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.21614497900009155}],"concepts":[{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.7797583341598511},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7408198118209839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5856115221977234},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5396734476089478},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4905380606651306},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4472436308860779},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42083853483200073},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.21614497900009155},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p17-1061","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1061","pdf_url":"https://www.aclweb.org/anthology/P17-1061.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\n          Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p17-1061","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p17-1061","pdf_url":"https://www.aclweb.org/anthology/P17-1061.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\n          Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2962717182.pdf","grobid_xml":"https://content.openalex.org/works/W2962717182.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W178897730","https://openalex.org/W1518951372","https://openalex.org/W1521626219","https://openalex.org/W1522301498","https://openalex.org/W1582147469","https://openalex.org/W1591706642","https://openalex.org/W1591801644","https://openalex.org/W1596717185","https://openalex.org/W1880262756","https://openalex.org/W1909320841","https://openalex.org/W1924770834","https://openalex.org/W1958706068","https://openalex.org/W1959608418","https://openalex.org/W1978394996","https://openalex.org/W2094484179","https://openalex.org/W2101105183","https://openalex.org/W2128970689","https://openalex.org/W2130942839","https://openalex.org/W2131774270","https://openalex.org/W2143177362","https://openalex.org/W2187089797","https://openalex.org/W2188365844","https://openalex.org/W2210838531","https://openalex.org/W2250539671","https://openalex.org/W2328886022","https://openalex.org/W2404576907","https://openalex.org/W2412899141","https://openalex.org/W2438667436","https://openalex.org/W2470875822","https://openalex.org/W2515741950","https://openalex.org/W2565274151","https://openalex.org/W2962776659","https://openalex.org/W2962883855","https://openalex.org/W2963167310","https://openalex.org/W2963206148","https://openalex.org/W2963223306","https://openalex.org/W2963567641","https://openalex.org/W2963620441","https://openalex.org/W2963790827","https://openalex.org/W2963903950","https://openalex.org/W2964121744","https://openalex.org/W2964352131","https://openalex.org/W3022187094","https://openalex.org/W4234134528","https://openalex.org/W4293919858","https://openalex.org/W4320013820"],"related_works":["https://openalex.org/W2098987383","https://openalex.org/W2417260800","https://openalex.org/W2795961259","https://openalex.org/W1596203174","https://openalex.org/W2117933979","https://openalex.org/W4298396513","https://openalex.org/W2283130723","https://openalex.org/W103938586","https://openalex.org/W2104718772","https://openalex.org/W4233992201"],"abstract_inverted_index":{"While":[0],"recent":[1],"neural":[2],"encoder-decoder":[3],"models":[4,108],"have":[5,79,109],"shown":[6],"great":[7],"promise":[8],"in":[9,54,124],"modeling":[10],"open-domain":[11],"conversations,":[12],"they":[13],"often":[14],"generate":[15,113],"dull":[16],"and":[17,70,121],"generic":[18],"responses.":[19],"Unlike":[20],"past":[21],"work":[22],"that":[23,49,85],"has":[24],"focused":[25],"on":[26,45],"diversifying":[27],"the":[28,31,51,55,96],"output":[29],"of":[30],"decoder":[32],"at":[33],"word-level":[34],"to":[35,62,112],"alleviate":[36],"this":[37],"problem,":[38],"we":[39],"present":[40],"a":[41,64,82,103],"novel":[42,83],"framework":[43],"based":[44],"conditional":[46],"variational":[47],"autoencoders":[48],"captures":[50],"discourse-level":[52,125],"diversity":[53],"encoder.":[56],"Our":[57,106],"model":[58],"uses":[59],"latent":[60],"variables":[61],"learn":[63],"distribution":[65],"over":[66],"potential":[67],"conversational":[68],"intents":[69],"generates":[71],"diverse":[72,116],"responses":[73,117],"using":[74],"only":[75],"greedy":[76],"decoders.":[77],"We":[78],"further":[80],"developed":[81],"variant":[84],"is":[86,99],"integrated":[87],"with":[88],"linguistic":[89],"prior":[90],"knowledge":[91],"for":[92],"better":[93],"performance.":[94],"Finally,":[95],"training":[97],"procedure":[98],"improved":[100],"by":[101],"introducing":[102],"bag-of-word":[104],"loss.":[105],"proposed":[107],"been":[110],"validated":[111],"significantly":[114],"more":[115],"than":[118],"baseline":[119],"approaches":[120],"exhibit":[122],"competence":[123],"decision-making.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":76},{"year":2022,"cited_by_count":91},{"year":2021,"cited_by_count":119},{"year":2020,"cited_by_count":176},{"year":2019,"cited_by_count":149},{"year":2018,"cited_by_count":47},{"year":2017,"cited_by_count":5}],"updated_date":"2026-06-18T10:00:31.954636","created_date":"2025-10-10T00:00:00"}