{"id":"https://openalex.org/W2950662536","doi":"https://doi.org/10.18653/v1/w19-5904","title":"Few-Shot Dialogue Generation Without Annotated Data: A Transfer Learning Approach","display_name":"Few-Shot Dialogue Generation Without Annotated Data: A Transfer Learning Approach","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2950662536","doi":"https://doi.org/10.18653/v1/w19-5904","mag":"2950662536"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w19-5904","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5904","pdf_url":"https://www.aclweb.org/anthology/W19-5904.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 20th Annual SIGdial Meeting on Discourse and Dialogue","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W19-5904.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011132902","display_name":"Igor Shalyminov","orcid":"https://orcid.org/0000-0001-9664-1774"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["GB","US"],"is_corresponding":true,"raw_author_name":"Igor Shalyminov","raw_affiliation_strings":["Heriot-Watt University, UK","Microsoft (United States), Redmond, United States"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University, UK","institution_ids":["https://openalex.org/I32062511"]},{"raw_affiliation_string":"Microsoft (United States), Redmond, United States","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100720086","display_name":"Sung\u2010Jin Lee","orcid":"https://orcid.org/0000-0001-9348-8356"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]},{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Sungjin Lee","raw_affiliation_strings":["Microsoft Research, US","Microsoft (United States), Redmond, United States"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, US","institution_ids":["https://openalex.org/I4210164937"]},{"raw_affiliation_string":"Microsoft (United States), Redmond, United States","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013679563","display_name":"Arash Eshghi","orcid":"https://orcid.org/0000-0003-4711-4091"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Arash Eshghi","raw_affiliation_strings":["Heriot-Watt University, UK","Heriot-Watt University, Edinburgh, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University, UK","institution_ids":["https://openalex.org/I32062511"]},{"raw_affiliation_string":"Heriot-Watt University, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010949145","display_name":"Oliver Lemon","orcid":"https://orcid.org/0000-0001-9497-4743"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Oliver Lemon","raw_affiliation_strings":["Heriot-Watt University, UK","Heriot-Watt University, Edinburgh, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Heriot-Watt University, UK","institution_ids":["https://openalex.org/I32062511"]},{"raw_affiliation_string":"Heriot-Watt University, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I32062511"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011132902"],"corresponding_institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I32062511"],"apc_list":null,"apc_paid":null,"fwci":1.1573,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84120255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"32","last_page":"39"},"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/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":0.9988999962806702,"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":0.8446377515792847},{"id":"https://openalex.org/keywords/open-domain","display_name":"Open domain","score":0.7203797698020935},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.669503927230835},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6209848523139954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6162565350532532},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5700819492340088},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5065950155258179},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.4833188056945801},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48104098439216614},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.47300201654434204},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4460570812225342},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42445695400238037},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3265710771083832},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.1648944616317749}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8446377515792847},{"id":"https://openalex.org/C2993776861","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Open domain","level":3,"score":0.7203797698020935},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.669503927230835},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6209848523139954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6162565350532532},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5700819492340088},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5065950155258179},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.4833188056945801},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48104098439216614},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.47300201654434204},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4460570812225342},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42445695400238037},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3265710771083832},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.1648944616317749},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.18653/v1/w19-5904","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5904","pdf_url":"https://www.aclweb.org/anthology/W19-5904.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 20th Annual SIGdial Meeting on Discourse and Dialogue","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1908.05854","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.05854","pdf_url":"https://arxiv.org/pdf/1908.05854","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2950662536","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1908.05854v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1908.05854","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1908.05854","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:3180770296","is_oa":false,"landing_page_url":"https://www.microsoft.com/en-us/research/publication/few-shot-dialogue-generation-without-annotated-data-a-transfer-learning-approach/","pdf_url":null,"source":{"id":"https://openalex.org/S4306418013","display_name":"Conference of the International Speech Communication Association","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Conference of the International Speech Communication Association","raw_type":null}],"best_oa_location":{"id":"doi:10.18653/v1/w19-5904","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w19-5904","pdf_url":"https://www.aclweb.org/anthology/W19-5904.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 20th Annual SIGdial Meeting on Discourse and Dialogue","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2950662536.pdf","grobid_xml":"https://content.openalex.org/works/W2950662536.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1793121960","https://openalex.org/W1993567041","https://openalex.org/W2064675550","https://openalex.org/W2096765155","https://openalex.org/W2108598243","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2251758222","https://openalex.org/W2277540893","https://openalex.org/W2583923862","https://openalex.org/W2889540167","https://openalex.org/W2943737083","https://openalex.org/W2962739339","https://openalex.org/W2963074876","https://openalex.org/W2963123621","https://openalex.org/W2963134326","https://openalex.org/W2963341956","https://openalex.org/W2963411289","https://openalex.org/W2963491014","https://openalex.org/W2963672599","https://openalex.org/W2963827272","https://openalex.org/W2964121744"],"related_works":["https://openalex.org/W2979714393","https://openalex.org/W3111288944","https://openalex.org/W3129255550","https://openalex.org/W3212259741","https://openalex.org/W2891732163","https://openalex.org/W3170116649","https://openalex.org/W3121272494","https://openalex.org/W3019510943","https://openalex.org/W2903655137","https://openalex.org/W3035565536","https://openalex.org/W3091938162","https://openalex.org/W3107013681","https://openalex.org/W3150234497","https://openalex.org/W3162400235","https://openalex.org/W3208068273","https://openalex.org/W2951147191","https://openalex.org/W3195654680","https://openalex.org/W3034987881","https://openalex.org/W2893314940","https://openalex.org/W3212893438"],"abstract_inverted_index":{"Learning":[0],"with":[1],"minimal":[2],"data":[3],"is":[4],"one":[5],"of":[6,13,40,51],"the":[7,11],"key":[8],"challenges":[9],"in":[10],"development":[12],"practical,":[14],"production-ready":[15],"goal-oriented":[16],"dialogue":[17,25],"systems.":[18],"In":[19],"a":[20,48],"real-world":[21],"enterprise":[22],"setting":[23],"where":[24],"systems":[26],"are":[27,31],"developed":[28],"rapidly":[29],"and":[30,43],"expected":[32],"to":[33],"work":[34],"robustly":[35],"for":[36],"an":[37],"evergrowing":[38],"variety":[39],"domains,":[41],"products,":[42],"scenarios,":[44],"efficient":[45],"learning":[46],"from":[47],"limited":[49],"number":[50],"examples":[52],"becomes":[53],"indispensable.":[54]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}