{"id":"https://openalex.org/W3204033710","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534385","title":"Hierarchical Dialogue State Tracking with Machine Reading Comprehension","display_name":"Hierarchical Dialogue State Tracking with Machine Reading Comprehension","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3204033710","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534385","mag":"3204033710"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086341816","display_name":"Boyu Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Boyu Qiu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016973102","display_name":"Jungang Xu","orcid":"https://orcid.org/0000-0002-3994-1401"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jungang Xu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103211417","display_name":"Yingfei Sun","orcid":"https://orcid.org/0000-0003-0615-2569"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfei Sun","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086341816"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14208758,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"abs 1910 3544","issue":null,"first_page":"1","last_page":"6"},"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/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":0.9930999875068665,"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/leverage","display_name":"Leverage (statistics)","score":0.7969798445701599},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7797520756721497},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5540550947189331},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5263128280639648},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.5221132040023804},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.5008387565612793},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4757910966873169},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.46583905816078186},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.41636693477630615},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3940775394439697},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.3469982147216797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32146626710891724},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11127308011054993},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10482543706893921},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07947567105293274}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7969798445701599},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7797520756721497},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5540550947189331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5263128280639648},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.5221132040023804},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.5008387565612793},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4757910966873169},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.46583905816078186},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.41636693477630615},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3940775394439697},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.3469982147216797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32146626710891724},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11127308011054993},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10482543706893921},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07947567105293274},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534385","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534385","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1544827683","https://openalex.org/W2250297846","https://openalex.org/W2250539671","https://openalex.org/W2551396370","https://openalex.org/W2556468274","https://openalex.org/W2798367796","https://openalex.org/W2896457183","https://openalex.org/W2945475330","https://openalex.org/W2949615363","https://openalex.org/W2954492830","https://openalex.org/W2963283951","https://openalex.org/W2963323070","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963748441","https://openalex.org/W2963797754","https://openalex.org/W2964006684","https://openalex.org/W2964101860","https://openalex.org/W2964121744","https://openalex.org/W2970597249","https://openalex.org/W2979400990","https://openalex.org/W2988252747","https://openalex.org/W2998432370","https://openalex.org/W3015637204","https://openalex.org/W3035594326","https://openalex.org/W3045689439","https://openalex.org/W3119649668","https://openalex.org/W4288027128","https://openalex.org/W4288094254","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6632455782","https://openalex.org/W6718074661","https://openalex.org/W6729654139","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6763701032","https://openalex.org/W6768747623"],"related_works":["https://openalex.org/W2085384747","https://openalex.org/W2088166309","https://openalex.org/W1891216533","https://openalex.org/W4312133475","https://openalex.org/W4238976562","https://openalex.org/W2369219372","https://openalex.org/W2082296339","https://openalex.org/W2161828220","https://openalex.org/W1972348076","https://openalex.org/W2083863157"],"abstract_inverted_index":{"In":[0,67],"task-oriented":[1],"dialogue":[2,4],"systems,":[3],"state":[5,15],"tracking":[6],"(DST)":[7],"is":[8],"responsible":[9],"for":[10],"estimating":[11],"the":[12,28,41,49,52,56,64,100,103,113,132],"current":[13,53],"belief":[14],"of":[16,32,102],"a":[17,96],"dialogue.":[18],"Recent":[19],"research":[20],"tends":[21],"to":[22,26,39,83,94,111],"utilize":[23],"historical":[24],"information":[25],"predict":[27,112],"states.":[29,114],"However,":[30],"most":[31],"them":[33],"lack":[34],"an":[35,72],"efficient":[36],"attention":[37,92],"mechanism":[38],"comprehend":[40],"utterances":[42,54],"well.":[43],"Besides,":[44],"existing":[45],"methods":[46],"usually":[47],"ignore":[48],"relevance":[50],"between":[51],"with":[55,78,131],"earlier":[57],"ones,":[58],"which":[59],"determines":[60],"whether":[61],"or":[62],"not":[63],"states":[65],"change.":[66],"this":[68],"paper,":[69],"we":[70,89],"propose":[71],"HDST-MRC":[73],"(Hierarchical":[74],"Dialogue":[75],"State":[76],"Tracking":[77],"Machine":[79],"Reading":[80],"Comprehension)":[81],"model":[82,126],"tackle":[84],"these":[85],"issues.":[86],"Within":[87],"HSDT-MRC,":[88],"introduce":[90],"bi-directional":[91],"flow":[93],"extract":[95],"context":[97],"span":[98],"as":[99],"evidence":[101],"ground":[104],"truth":[105],"and":[106,120],"leverage":[107],"another":[108],"copy-augmented":[109],"generator":[110],"Experimental":[115],"results":[116],"on":[117],"MultiWoz":[118,121],"2.0":[119],"2.1":[122],"demonstrate":[123],"that":[124],"our":[125],"achieves":[127],"significant":[128],"improvement":[129],"compared":[130],"baselines.":[133]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
