{"id":"https://openalex.org/W3162521862","doi":"https://doi.org/10.1109/icassp39728.2021.9413908","title":"Adversarial Generative Distance-Based Classifier for Robust Out-of-Domain Detection","display_name":"Adversarial Generative Distance-Based Classifier for Robust Out-of-Domain Detection","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3162521862","doi":"https://doi.org/10.1109/icassp39728.2021.9413908","mag":"3162521862"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9413908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5075168326","display_name":"Zhiyuan Zeng","orcid":"https://orcid.org/0000-0002-3979-3322"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Zeng","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084983727","display_name":"Hong Xu","orcid":"https://orcid.org/0000-0001-7874-4518"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101887051","display_name":"Keqing He","orcid":"https://orcid.org/0000-0002-7554-3638"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keqing He","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030878947","display_name":"Yuanmeng Yan","orcid":"https://orcid.org/0000-0002-0400-4522"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanmeng Yan","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085963057","display_name":"Sihong Liu","orcid":"https://orcid.org/0000-0002-5188-5334"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sihong Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100725226","display_name":"Zijun Liu","orcid":"https://orcid.org/0009-0005-0559-5677"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijun Liu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016651990","display_name":"Weiran Xu","orcid":"https://orcid.org/0000-0002-9416-7666"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiran Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":2.301,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.89553699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"7658","last_page":"7662"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10260","display_name":"Software Engineering Research","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9939000010490417,"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/discriminator","display_name":"Discriminator","score":0.8671063184738159},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.770707905292511},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7592806816101074},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6785197854042053},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6436278820037842},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6423888802528381},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5686764121055603},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5225400328636169},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4741358458995819},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.46109214425086975},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4399445056915283}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8671063184738159},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.770707905292511},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7592806816101074},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6785197854042053},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6436278820037842},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6423888802528381},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5686764121055603},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5225400328636169},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4741358458995819},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.46109214425086975},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4399445056915283},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9413908","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9413908","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1945616565","https://openalex.org/W2099471712","https://openalex.org/W2250539671","https://openalex.org/W2460937040","https://openalex.org/W2531327146","https://openalex.org/W2572102653","https://openalex.org/W2575298912","https://openalex.org/W2611138659","https://openalex.org/W2624172162","https://openalex.org/W2626967530","https://openalex.org/W2767414122","https://openalex.org/W2773244891","https://openalex.org/W2891642103","https://openalex.org/W2904981516","https://openalex.org/W2908350269","https://openalex.org/W2951883849","https://openalex.org/W2952409498","https://openalex.org/W2963098487","https://openalex.org/W2963149653","https://openalex.org/W2963207607","https://openalex.org/W2963384319","https://openalex.org/W2963693742","https://openalex.org/W2963969444","https://openalex.org/W2964121744","https://openalex.org/W2964212410","https://openalex.org/W2964309167","https://openalex.org/W2970946347","https://openalex.org/W2986193249","https://openalex.org/W3014773921","https://openalex.org/W3093419064","https://openalex.org/W4300511536","https://openalex.org/W4300996741","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6640425456","https://openalex.org/W6719080892","https://openalex.org/W6728622933","https://openalex.org/W6730161283","https://openalex.org/W6739144152","https://openalex.org/W6739651123","https://openalex.org/W6745553787","https://openalex.org/W6745891213","https://openalex.org/W6757453587","https://openalex.org/W6757615711","https://openalex.org/W6762924995"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W4380714744","https://openalex.org/W2387995142","https://openalex.org/W2995777218","https://openalex.org/W4289106901","https://openalex.org/W2951387371","https://openalex.org/W2596763562","https://openalex.org/W2964218010"],"abstract_inverted_index":{"Detecting":[0],"out-of-domain":[1],"(OOD)":[2],"intents":[3],"is":[4],"critical":[5],"in":[6],"a":[7,41,52,73],"task-oriented":[8],"dialog":[9],"system.":[10],"Existing":[11],"methods":[12],"rely":[13],"heavily":[14],"on":[15,58],"extensive":[16],"manually":[17],"labeled":[18],"OOD":[19,37,48],"samples":[20,38,49],"and":[21,39],"lack":[22],"robustness.":[23],"In":[24],"this":[25],"paper,":[26],"we":[27],"propose":[28],"an":[29],"efficient":[30],"adversarial":[31],"attack":[32],"mechanism":[33],"to":[34,46],"augment":[35],"hard":[36],"design":[40],"novel":[42],"generative":[43],"distance-based":[44],"classifier":[45],"detect":[47],"instead":[50],"of":[51],"traditional":[53],"threshold-based":[54],"discriminator":[55],"classifier.":[56],"Experiments":[57],"two":[59],"public":[60],"benchmark":[61],"datasets":[62],"show":[63],"that":[64],"our":[65],"method":[66],"can":[67],"consistently":[68],"outperform":[69],"the":[70],"baselines":[71],"with":[72],"statistically":[74],"significant":[75],"margin.":[76]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}