{"id":"https://openalex.org/W2759438615","doi":"https://doi.org/10.18653/v1/d17-1236","title":"Bootstrapping incremental dialogue systems from minimal data: the generalisation power of dialogue grammars","display_name":"Bootstrapping incremental dialogue systems from minimal data: the generalisation power of dialogue grammars","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2759438615","doi":"https://doi.org/10.18653/v1/d17-1236","mag":"2759438615"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1236","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1236","pdf_url":"https://www.aclweb.org/anthology/D17-1236.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","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/D17-1236.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013679563","display_name":"Arash Eshghi","orcid":"https://orcid.org/0000-0003-4711-4091"},"institutions":[{"id":"https://openalex.org/I4210085930","display_name":"Heriot-Watt University Malaysia","ror":"https://ror.org/0059w0420","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210085930"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Arash Eshghi","raw_affiliation_strings":["Interaction Lab Heriot-Watt University","Computer Science"],"affiliations":[{"raw_affiliation_string":"Interaction Lab Heriot-Watt University","institution_ids":["https://openalex.org/I4210085930"]},{"raw_affiliation_string":"Computer Science","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011132902","display_name":"Igor Shalyminov","orcid":"https://orcid.org/0000-0001-9664-1774"},"institutions":[{"id":"https://openalex.org/I4210085930","display_name":"Heriot-Watt University Malaysia","ror":"https://ror.org/0059w0420","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210085930"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Igor Shalyminov","raw_affiliation_strings":["Interaction Lab Heriot-Watt University","Computer Science"],"affiliations":[{"raw_affiliation_string":"Interaction Lab Heriot-Watt University","institution_ids":["https://openalex.org/I4210085930"]},{"raw_affiliation_string":"Computer Science","institution_ids":[]}]},{"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/I4210085930","display_name":"Heriot-Watt University Malaysia","ror":"https://ror.org/0059w0420","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210085930"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Oliver Lemon","raw_affiliation_strings":["Interaction Lab Heriot-Watt University","Computer Science"],"affiliations":[{"raw_affiliation_string":"Interaction Lab Heriot-Watt University","institution_ids":["https://openalex.org/I4210085930"]},{"raw_affiliation_string":"Computer Science","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013679563"],"corresponding_institution_ids":["https://openalex.org/I4210085930"],"apc_list":null,"apc_paid":null,"fwci":1.0393,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.83531493,"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":"2220","last_page":"2230"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.8012545108795166},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.6598941683769226},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6405888795852661},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6401157379150391},{"id":"https://openalex.org/keywords/rule-based-machine-translation","display_name":"Rule-based machine translation","score":0.5941520929336548},{"id":"https://openalex.org/keywords/grammar","display_name":"Grammar","score":0.5057721138000488},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.502765417098999},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.48969557881355286},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.44941624999046326},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4452960789203644},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.20383164286613464},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08890363574028015}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8012545108795166},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.6598941683769226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6405888795852661},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6401157379150391},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.5941520929336548},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.5057721138000488},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.502765417098999},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.48969557881355286},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.44941624999046326},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4452960789203644},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.20383164286613464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08890363574028015},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/d17-1236","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1236","pdf_url":"https://www.aclweb.org/anthology/D17-1236.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1709.07858","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.07858","pdf_url":"https://arxiv.org/pdf/1709.07858","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:2759438615","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1709.07858.pdf","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.1709.07858","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1709.07858","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-journal"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1236","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1236","pdf_url":"https://www.aclweb.org/anthology/D17-1236.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G4170278468","display_name":null,"funder_award_id":"EP/M01553X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5678719568","display_name":"Babble: domain-general methods for learning natural spoken dialogue systems","funder_award_id":"EP/M01553X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2759438615.pdf","grobid_xml":"https://content.openalex.org/works/W2759438615.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1475427439","https://openalex.org/W1487640415","https://openalex.org/W1491700729","https://openalex.org/W1541013760","https://openalex.org/W1560002237","https://openalex.org/W2115733720","https://openalex.org/W2120614088","https://openalex.org/W2122702954","https://openalex.org/W2126814423","https://openalex.org/W2250653987","https://openalex.org/W2254658406","https://openalex.org/W2277540893","https://openalex.org/W2291723583","https://openalex.org/W2339361964","https://openalex.org/W2739512085","https://openalex.org/W2766929078","https://openalex.org/W2775225875","https://openalex.org/W2911595932","https://openalex.org/W2963827272"],"related_works":["https://openalex.org/W2963074876","https://openalex.org/W2739512085","https://openalex.org/W2559882885","https://openalex.org/W3087176213","https://openalex.org/W3149442855","https://openalex.org/W3208280523","https://openalex.org/W2122514299","https://openalex.org/W3214233532","https://openalex.org/W3090746051","https://openalex.org/W2398742098","https://openalex.org/W3086380466","https://openalex.org/W2910795780","https://openalex.org/W3208630568","https://openalex.org/W2785952547","https://openalex.org/W2892354565","https://openalex.org/W2096831027","https://openalex.org/W2151691130","https://openalex.org/W2888175818","https://openalex.org/W2160581145","https://openalex.org/W2096968458"],"abstract_inverted_index":{"We":[0,67,148,158],"investigate":[1],"an":[2,20],"end-to-end":[3],"method":[4],"for":[5],"automatically":[6],"inducing":[7],"task-based":[8],"dialogue":[9,16,40,84,139],"systems":[10,48],"from":[11],"small":[12],"amounts":[13],"of":[14,83,105,117,128,163],"unannotated":[15],"data.":[17],"It":[18,122],"combines":[19],"incremental":[21,138],"semantic":[22,164],"grammar":[23,76],"-Dynamic":[24],"Syntax":[25],"and":[26,39,144],"Type":[27],"Theory":[28],"with":[29,152],"Records":[30],"(DS-TTR)":[31],"-with":[32],"Reinforcement":[33],"Learning":[34],"(RL),":[35],"where":[36],"language":[37],"generation":[38],"management":[41],"are":[42,51,54],"a":[43,79,130,153],"joint":[44],"decision":[45],"problem.":[46],"The":[47],"thus":[49],"produced":[50],"incremental:":[52],"dialogues":[53],"processed":[55],"word-by-word,":[56],"shown":[57],"previously":[58],"to":[59,86,146,171],"be":[60,87],"essential":[61],"in":[62,124,161],"supporting":[63],"natural,":[64],"spontaneous":[65],"dialogue.":[66],"hypothesised":[68],"that":[69,99],"the":[70,75,106,118,172,179],"rich":[71],"linguistic":[72],"knowledge":[73],"within":[74],"should":[77],"enable":[78],"combinatorially":[80],"large":[81],"number":[82],"variations":[85],"processed,":[88],"even":[89,111,175],"when":[90,112,176],"trained":[91,113,177],"on":[92,114,178],"very":[93,168],"few":[94],"dialogues.":[95],"Our":[96],"experiments":[97],"show":[98],"our":[100,150],"model":[101,151],"can":[102,123],"process":[103,126],"74%":[104],"Facebook":[107],"AI":[108],"bAbI":[109,181],"dataset":[110],"only":[115],"0.13%":[116],"data":[119],"(5":[120],"dialogues).":[121],"addition":[125],"65%":[127],"bAbI+,":[129],"corpus":[131],"1":[132],"we":[133],"created":[134],"by":[135],"systematically":[136],"adding":[137],"phenomena":[140],"such":[141],"as":[142],"restarts":[143],"self-corrections":[145],"bAbI.":[147],"compare":[149],"state-of-theart":[154],"retrieval":[155],"model,":[156],"memn2n":[157,166],"find":[159],"that,":[160],"terms":[162],"accuracy,":[165],"shows":[167],"poor":[169],"robustness":[170],"bAbI+":[173],"transformations":[174],"full":[180],"dataset.":[182]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}