{"id":"https://openalex.org/W2963283951","doi":"https://doi.org/10.18653/v1/p18-1134","title":"An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking","display_name":"An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2963283951","doi":"https://doi.org/10.18653/v1/p18-1134","mag":"2963283951"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-1134","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1134","pdf_url":"https://www.aclweb.org/anthology/P18-1134.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 56th Annual Meeting of the Association for 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/P18-1134.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113753678","display_name":"Puyang Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Puyang Xu","raw_affiliation_strings":["Mobvoi AI Lab, Redmond, WA"],"affiliations":[{"raw_affiliation_string":"Mobvoi AI Lab, Redmond, WA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101949451","display_name":"Qi Hu","orcid":"https://orcid.org/0000-0002-8676-2297"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Hu","raw_affiliation_strings":["University of Washington, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5113753678"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.2203,"has_fulltext":true,"cited_by_count":149,"citation_normalized_percentile":{"value":0.99363668,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12031","display_name":"Speech and dialogue systems","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/T12031","display_name":"Speech and dialogue systems","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/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.996399998664856,"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/end-to-end-principle","display_name":"End-to-end principle","score":0.7778880000114441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7739531993865967},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.7495713829994202},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.737109899520874},{"id":"https://openalex.org/keywords/pointer","display_name":"Pointer (user interface)","score":0.5999935865402222},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4974236786365509},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.49232470989227295},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.48793908953666687},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41957247257232666},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4100792407989502},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3435802459716797},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33647096157073975},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20736467838287354}],"concepts":[{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.7778880000114441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7739531993865967},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.7495713829994202},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.737109899520874},{"id":"https://openalex.org/C150202949","wikidata":"https://www.wikidata.org/wiki/Q107602","display_name":"Pointer (user interface)","level":2,"score":0.5999935865402222},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4974236786365509},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.49232470989227295},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.48793908953666687},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41957247257232666},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4100792407989502},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3435802459716797},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33647096157073975},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20736467838287354},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p18-1134","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1134","pdf_url":"https://www.aclweb.org/anthology/P18-1134.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p18-1134","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-1134","pdf_url":"https://www.aclweb.org/anthology/P18-1134.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 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963283951.pdf","grobid_xml":"https://content.openalex.org/works/W2963283951.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W648947103","https://openalex.org/W1522301498","https://openalex.org/W1904365287","https://openalex.org/W2115090890","https://openalex.org/W2250297846","https://openalex.org/W2251058040","https://openalex.org/W2251163406","https://openalex.org/W2251235149","https://openalex.org/W2396928039","https://openalex.org/W2412715517","https://openalex.org/W2507756961","https://openalex.org/W2516930406","https://openalex.org/W2606974598","https://openalex.org/W2772001136","https://openalex.org/W2949252816","https://openalex.org/W2962776342","https://openalex.org/W2962847367","https://openalex.org/W2962886331","https://openalex.org/W2962944953","https://openalex.org/W2963068985","https://openalex.org/W2963243930","https://openalex.org/W2963788376","https://openalex.org/W2963797754","https://openalex.org/W2964057895","https://openalex.org/W2964101860","https://openalex.org/W2964121744","https://openalex.org/W2964165364","https://openalex.org/W2964210218","https://openalex.org/W3037881859","https://openalex.org/W4295249402"],"related_works":["https://openalex.org/W3082178636","https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W1521968289","https://openalex.org/W4321353415","https://openalex.org/W2782041652","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2963789888"],"abstract_inverted_index":{"We":[0,50,81],"highlight":[1],"a":[2],"practical":[3],"yet":[4],"rarely":[5],"discussed":[6],"problem":[7],"in":[8,45,52],"dialogue":[9],"state":[10],"tracking":[11,90],"(DST),":[12],"namely":[13],"handling":[14],"unknown":[15,32,68,91],"slot":[16,69],"values.":[17],"Previous":[18],"approaches":[19],"generally":[20],"assume":[21],"predefined":[22],"candidate":[23],"lists":[24],"and":[25,96],"thus":[26],"are":[27],"not":[28],"designed":[29],"to":[30,87],"output":[31],"values,":[33],"especially":[34],"when":[35],"the":[36,60,77,104],"spoken":[37],"language":[38],"understanding":[39],"(SLU)":[40],"module":[41],"is":[42],"absent":[43],"as":[44],"many":[46],"end-to-end":[47],"(E2E)":[48],"systems.":[49],"describe":[51],"this":[53],"paper":[54],"an":[55,107],"E2E":[56],"architecture":[57],"based":[58],"on":[59,76],"pointer":[61],"network":[62],"(PtrNet)":[63],"that":[64,89],"can":[65,93,99],"effectively":[66],"extract":[67],"values":[70,92],"while":[71],"still":[72],"obtains":[73],"state-of-the-art":[74],"accuracy":[75],"standard":[78],"DSTC2":[79],"benchmark.":[80],"also":[82],"provide":[83],"extensive":[84],"empirical":[85],"evidence":[86],"show":[88],"be":[94],"challenging":[95],"our":[97],"approach":[98],"bring":[100],"significant":[101],"improvement":[102],"with":[103],"help":[105],"of":[106],"effective":[108],"feature":[109],"dropout":[110],"technique.":[111]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":35},{"year":2020,"cited_by_count":51},{"year":2019,"cited_by_count":27},{"year":2018,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}