{"id":"https://openalex.org/W3116903111","doi":"https://doi.org/10.18653/v1/2020.coling-main.364","title":"Diverse dialogue generation with context dependent dynamic loss function","display_name":"Diverse dialogue generation with context dependent dynamic loss function","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3116903111","doi":"https://doi.org/10.18653/v1/2020.coling-main.364","mag":"3116903111"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2020.coling-main.364","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.364","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 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/2020.coling-main.364","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019650689","display_name":"Ayaka Ueyama","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ayaka Ueyama","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5017969792","display_name":"Yoshinobu Kano","orcid":"https://orcid.org/0000-0001-7864-842X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoshinobu Kano","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019650689"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5302,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73994005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4123","last_page":"4127"},"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":0.9995999932289124,"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":0.9991999864578247,"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/softmax-function","display_name":"Softmax function","score":0.9010350108146667},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.6931048631668091},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6740567684173584},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.641289234161377},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48381513357162476},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.47460001707077026},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.46844059228897095},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4200386703014374},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.4179028272628784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41687431931495667},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.40033283829689026},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.22980350255966187},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.18441641330718994},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09314656257629395}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9010350108146667},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.6931048631668091},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6740567684173584},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.641289234161377},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48381513357162476},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.47460001707077026},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46844059228897095},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4200386703014374},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.4179028272628784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41687431931495667},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.40033283829689026},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.22980350255966187},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.18441641330718994},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09314656257629395},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2020.coling-main.364","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.364","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 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2020.coling-main.364","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.364","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 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1591706642","https://openalex.org/W1959608418","https://openalex.org/W2101105183","https://openalex.org/W2130942839","https://openalex.org/W2154652894","https://openalex.org/W2890969459","https://openalex.org/W2892153332","https://openalex.org/W2901950428","https://openalex.org/W2963035145","https://openalex.org/W2963206148","https://openalex.org/W2963223306","https://openalex.org/W2963250244","https://openalex.org/W2963403868","https://openalex.org/W2963963856","https://openalex.org/W2964121744","https://openalex.org/W2972603547"],"related_works":["https://openalex.org/W2250909759","https://openalex.org/W2532616038","https://openalex.org/W2787311093","https://openalex.org/W2268150819","https://openalex.org/W2057384730","https://openalex.org/W4307474317","https://openalex.org/W2147879411","https://openalex.org/W2624072012","https://openalex.org/W2008468404","https://openalex.org/W3049463507"],"abstract_inverted_index":{"Dialogue":[0],"systems":[1],"using":[2,70,101,110],"deep":[3],"learning":[4],"have":[5],"achieved":[6,138],"generation":[7],"of":[8,74,94,121,145],"fluent":[9],"response":[10],"sentences":[11],"to":[12,18,79],"user":[13],"utterances.":[14],"Nevertheless,":[15],"they":[16],"tend":[17],"produce":[19],"responses":[20],"that":[21,84],"are":[22,27],"not":[23],"diverse":[24],"and":[25,49,103,124,134,136,147],"which":[26,45],"less":[28],"context-dependent.":[29],"To":[30],"address":[31],"these":[32],"shortcomings,":[33],"we":[34],"propose":[35],"a":[36,56,68],"new":[37],"loss":[38,43,61,65,112,116,123,126],"function,":[39],"an":[40],"Inverse":[41],"N-gram":[42],"(INF),":[44],"incorporates":[46],"contextual":[47],"fluency":[48,93],"diversity":[50],"at":[51],"the":[52,71,75,92,95,119],"same":[53],"time":[54],"by":[55,67],"simple":[57],"formula.":[58],"Our":[59,114],"INF":[60,115],"can":[62],"adjust":[63],"its":[64],"dynamically":[66],"weight":[69],"inverse":[72],"frequency":[73],"tokens\u2019":[76],"n-gram":[77],"applied":[78],"Softmax":[80],"Cross-Entropy":[81],"loss,":[82],"so":[83],"rare":[85],"tokens":[86],"appear":[87],"more":[88],"likely":[89],"while":[90],"retaining":[91],"generated":[96],"sentences.":[97],"We":[98],"trained":[99],"Transformer":[100],"English":[102],"Japanese":[104],"Twitter":[105],"replies":[106],"as":[107,132],"single-turn":[108],"dialogues":[109],"different":[111],"functions.":[113],"model":[117],"outperformed":[118],"baselines":[120],"SCE":[122],"ITF":[125],"models":[127],"in":[128],"automatic":[129],"evaluations":[130,144],"such":[131],"DIST-N":[133],"ROUGE,":[135],"also":[137],"higher":[139],"scores":[140],"on":[141],"our":[142],"human":[143],"coherence":[146],"richness.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-02-02T03:55:41.653505","created_date":"2025-10-10T00:00:00"}
