{"id":"https://openalex.org/W2891704263","doi":"https://doi.org/10.18653/v1/d18-1419","title":"AirDialogue: An Environment for Goal-Oriented Dialogue Research","display_name":"AirDialogue: An Environment for Goal-Oriented Dialogue Research","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2891704263","doi":"https://doi.org/10.18653/v1/d18-1419","mag":"2891704263"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1419","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1419","pdf_url":"https://www.aclweb.org/anthology/D18-1419.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1419.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100323752","display_name":"Wei Wei","orcid":"https://orcid.org/0000-0002-7566-2995"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Wei","raw_affiliation_strings":["Google Cloud AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Cloud AI","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088551093","display_name":"Quoc V. Le","orcid":"https://orcid.org/0000-0002-1087-2844"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Quoc Le","raw_affiliation_strings":["Google Brain wewei, qvl, adai,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Brain wewei, qvl, adai,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029197877","display_name":"Andrew M. Dai","orcid":"https://orcid.org/0000-0002-7112-8277"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Dai","raw_affiliation_strings":["Google Brain wewei, qvl, adai,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Brain wewei, qvl, adai,","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009049500","display_name":"Li-Jia Li","orcid":"https://orcid.org/0000-0001-5850-7013"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jia Li","raw_affiliation_strings":["Google Cloud AI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Cloud AI","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5009049500"],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":49,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3844","last_page":"3854"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10028","display_name":"Topic Modeling","score":0.9941999912261963,"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.9922000169754028,"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":0.8349497318267822},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6338043212890625},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6253616809844971},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.5709049701690674},{"id":"https://openalex.org/keywords/ask-price","display_name":"Ask price","score":0.5468562841415405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.50681072473526},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4988739490509033},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.49037957191467285},{"id":"https://openalex.org/keywords/goal-orientation","display_name":"Goal orientation","score":0.4478861689567566}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8349497318267822},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6338043212890625},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6253616809844971},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5709049701690674},{"id":"https://openalex.org/C90329073","wikidata":"https://www.wikidata.org/wiki/Q914232","display_name":"Ask price","level":2,"score":0.5468562841415405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.50681072473526},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4988739490509033},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.49037957191467285},{"id":"https://openalex.org/C84653758","wikidata":"https://www.wikidata.org/wiki/Q5575175","display_name":"Goal orientation","level":2,"score":0.4478861689567566},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d18-1419","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1419","pdf_url":"https://www.aclweb.org/anthology/D18-1419.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1419","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1419","pdf_url":"https://www.aclweb.org/anthology/D18-1419.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 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2891704263.pdf","grobid_xml":"https://content.openalex.org/works/W2891704263.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1591706642","https://openalex.org/W1604513301","https://openalex.org/W1993378086","https://openalex.org/W2001771035","https://openalex.org/W2117989772","https://openalex.org/W2119717200","https://openalex.org/W2130942839","https://openalex.org/W2132997613","https://openalex.org/W2157331557","https://openalex.org/W2160458012","https://openalex.org/W2251058040","https://openalex.org/W2418993857","https://openalex.org/W2507756961","https://openalex.org/W2571927164","https://openalex.org/W2586847566","https://openalex.org/W2604698497","https://openalex.org/W2749436976","https://openalex.org/W2772001136","https://openalex.org/W2835434549","https://openalex.org/W2949252816","https://openalex.org/W2950902819","https://openalex.org/W2962707484","https://openalex.org/W2962852262","https://openalex.org/W2963167310","https://openalex.org/W2963206148","https://openalex.org/W2963217826","https://openalex.org/W2963324947","https://openalex.org/W2963491014","https://openalex.org/W2963797754","https://openalex.org/W2963963856","https://openalex.org/W2964210218","https://openalex.org/W4295249402"],"related_works":["https://openalex.org/W4210912933","https://openalex.org/W3209094908","https://openalex.org/W4206669594","https://openalex.org/W3005560120","https://openalex.org/W2506896584","https://openalex.org/W2963343509","https://openalex.org/W4312914540","https://openalex.org/W2617128460","https://openalex.org/W3196614708","https://openalex.org/W2161086704"],"abstract_inverted_index":{"Recent":[0],"progress":[1],"in":[2,49],"dialogue":[3,12,42,147,166],"generation":[4],"has":[5],"inspired":[6],"a":[7,66,80,98,111,175,191],"number":[8],"of":[9,17,33,97,108,123,127,178,185,193],"studies":[10,29],"on":[11,168],"systems":[13],"that":[14,69,149,164],"are":[15,47],"capable":[16],"accomplishing":[18],"tasks":[19],"through":[20],"natural":[21],"language":[22],"interactions.":[23],"A":[24],"promising":[25],"direction":[26],"among":[27],"these":[28],"is":[30,60,120,131,156],"the":[31,52,95,106,114,121,125,128,138,144,153,169],"use":[32],"reinforcement":[34],"learning":[35],"techniques,":[36],"such":[37],"as":[38],"self-play,":[39],"for":[40,54,202],"training":[41,55],"agents.":[43],"However,":[44],"current":[45],"datasets":[46],"limited":[48],"size,":[50],"and":[51,57,85,103,180,195],"environment":[53,119],"agents":[56],"evaluating":[58,124],"process":[59],"relatively":[61],"unsophisticated.":[62],"We":[63,88],"present":[64],"AirDialogue,":[65],"large":[67],"dataset":[68,171],"contains":[70],"402,038":[71],"goal-oriented":[72],"conversations.":[73],"To":[74],"collect":[75],"this":[76],"dataset,":[77],"we":[78],"create":[79],"contextgenerator":[81],"which":[82,130,198],"provides":[83],"travel":[84],"flight":[86,139],"restrictions.":[87,115,145],"then":[89],"ask":[90],"human":[91],"annotators":[92],"to":[93,117,158],"play":[94],"role":[96],"customer":[99],"or":[100],"an":[101,181],"agent":[102,148],"interact":[104],"with":[105],"goal":[107],"successfully":[109],"booking":[110],"trip":[112],"given":[113],"Key":[116],"our":[118],"ease":[122],"success":[126],"dialogue,":[129],"achieved":[132],"by":[133,143],"using":[134],"ground-truth":[135],"states":[136,155],"(e.g.,":[137],"being":[140],"booked)":[141],"generated":[142],"Any":[146],"does":[150],"not":[151],"generate":[152],"correct":[154],"considered":[157],"fail.":[159],"Our":[160],"experimental":[161],"results":[162],"indicate":[163],"state-of-the-art":[165],"models":[167],"test":[170],"can":[172,189],"only":[173],"achieve":[174],"scaled":[176],"score":[177,184,192],"0.22":[179],"exact":[182],"match":[183],"0.1":[186],"while":[187],"humans":[188],"reach":[190],"0.94":[194],"0.93":[196],"respectively,":[197],"suggests":[199],"significant":[200],"opportunities":[201],"future":[203],"improvement.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":10}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}