{"id":"https://openalex.org/W3200127966","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533361","title":"DCEN: A Decoupled Context Enhanced Network For Few-shot Slot Tagging","display_name":"DCEN: A Decoupled Context Enhanced Network For Few-shot Slot Tagging","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200127966","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533361","mag":"3200127966"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533361","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533361","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":"conference-paper","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/A5014639106","display_name":"Youliang Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youliang Yuan","raw_affiliation_strings":["School of Computer Science, Wuhan University, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005999583","display_name":"Jiaxin Pan","orcid":"https://orcid.org/0000-0002-7459-6850"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxin Pan","raw_affiliation_strings":["School of Computer Science, Wuhan University, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380896","display_name":"Jia Xu","orcid":"https://orcid.org/0000-0002-1996-0162"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Jia","raw_affiliation_strings":["Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074524814","display_name":"Luchen Liu","orcid":"https://orcid.org/0009-0009-3817-6267"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luchen Liu","raw_affiliation_strings":["School of Computer Science, Wuhan University, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114778045","display_name":"Min Peng","orcid":"https://orcid.org/0000-0002-8766-1105"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Peng","raw_affiliation_strings":["School of Computer Science, Wuhan University, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1","last_page":"7"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9993000030517578,"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":0.8356397151947021},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6274312734603882},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5605961084365845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49753978848457336},{"id":"https://openalex.org/keywords/context-model","display_name":"Context model","score":0.4665123522281647},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.46104997396469116},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.4364733099937439}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8356397151947021},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6274312734603882},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5605961084365845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49753978848457336},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.4665123522281647},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.46104997396469116},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.4364733099937439},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","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},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533361","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533361","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":[],"awards":[{"id":"https://openalex.org/G6700869451","display_name":null,"funder_award_id":"2018YFC1604003","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2024632416","https://openalex.org/W2094472029","https://openalex.org/W2115733720","https://openalex.org/W2131774270","https://openalex.org/W2137871902","https://openalex.org/W2147880316","https://openalex.org/W2250539671","https://openalex.org/W2601450892","https://openalex.org/W2793556064","https://openalex.org/W2799010330","https://openalex.org/W2803609229","https://openalex.org/W2804945011","https://openalex.org/W2891533927","https://openalex.org/W2896457183","https://openalex.org/W2904415434","https://openalex.org/W2949325756","https://openalex.org/W2950763986","https://openalex.org/W2951088751","https://openalex.org/W2963066655","https://openalex.org/W2963341924","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963578915","https://openalex.org/W2963974889","https://openalex.org/W2964071174","https://openalex.org/W2964105864","https://openalex.org/W2964121744","https://openalex.org/W2964236684","https://openalex.org/W2971048662","https://openalex.org/W2971167298","https://openalex.org/W3034445880","https://openalex.org/W3035044482","https://openalex.org/W3035371495","https://openalex.org/W3087547404","https://openalex.org/W3099591453","https://openalex.org/W3161463965","https://openalex.org/W4297683418","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6739901393","https://openalex.org/W6751425476","https://openalex.org/W6755207826","https://openalex.org/W6763315676","https://openalex.org/W6783265340","https://openalex.org/W6784676410"],"related_works":["https://openalex.org/W2349222429","https://openalex.org/W2116230991","https://openalex.org/W3117430770","https://openalex.org/W2046058552","https://openalex.org/W2590751808","https://openalex.org/W1972377868","https://openalex.org/W2132709506","https://openalex.org/W2098730537","https://openalex.org/W2186895195","https://openalex.org/W2748557612"],"abstract_inverted_index":{"Few-shot":[0],"slot":[1,14,58,77,93],"tagging":[2,15],"is":[3],"an":[4,18],"important":[5],"task":[6],"in":[7,60,96],"developing":[8],"dialogue":[9],"system.":[10],"Most":[11],"previous":[12,81],"few-shot":[13,61,76],"models":[16,31],"classify":[17],"item":[19],"according":[20],"to":[21,24,88,115,133],"its":[22],"similarity":[23],"the":[25,42,54,69,97,149],"representation":[26],"of":[27,46,56,92],"each":[28,37],"class.":[29],"These":[30],"leverage":[32],"context":[33,51,86,100,108,119],"information":[34,122,137],"implicitly":[35],"through":[36],"words'":[38],"contextual":[39],"embedding.":[40],"However,":[41],"entangled":[43],"language":[44],"features":[45,59,94],"words":[47],"may":[48],"interfere":[49],"with":[50,152],"information,":[52],"misleading":[53],"utilization":[55],"crucial":[57],"scenario.":[62],"To":[63],"tackle":[64],"these":[65],"problems,":[66],"we":[67,83],"propose":[68],"Decoupled":[70,99],"Context":[71],"Enhanced":[72],"Network":[73],"(DCEN)":[74],"for":[75],"tagging.":[78],"Different":[79],"from":[80,123],"models,":[82],"extract":[84,116,134],"decoupled":[85,107,118,136],"explicitly":[87],"make":[89],"full":[90],"use":[91],"contained":[95],"context.":[98],"includes":[101],"two":[102],"parts,":[103],"local":[104,113,117],"and":[105,126],"global":[106,128,135],"information.":[109],"We":[110],"introduce":[111],"a":[112,127],"extractor":[114,129],"by":[120,138],"integrating":[121],"adjacent":[124],"words,":[125],"based":[130],"on":[131,142],"transformer":[132],"orthogonalization.":[139],"Experimental":[140],"results":[141],"SNIPS":[143],"show":[144],"that":[145],"our":[146],"model":[147],"achieves":[148],"state-of-the-art":[150],"performance":[151],"considerable":[153],"improvements.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}