{"id":"https://openalex.org/W4402353615","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651377","title":"Towards Robustness and Diversity: Continual Learning in Dialog Generation with Text-Mixup and Batch Nuclear-Norm Maximization","display_name":"Towards Robustness and Diversity: Continual Learning in Dialog Generation with Text-Mixup and Batch Nuclear-Norm Maximization","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402353615","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651377"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5100380108","display_name":"Zihan Wang","orcid":"https://orcid.org/0000-0003-1056-6326"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zihan Wang","raw_affiliation_strings":["China Telecom Corporation Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"China Telecom Corporation Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069689204","display_name":"Jiayu Xiao","orcid":"https://orcid.org/0000-0001-7478-6534"},"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":"Jiayu Xiao","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/A5102706632","display_name":"Mengxiang Li","orcid":"https://orcid.org/0000-0003-4411-239X"},"institutions":[{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]},{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengxiang Li","raw_affiliation_strings":["China Telecom Corporation Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"China Telecom Corporation Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101722779","display_name":"Zhongjiang He","orcid":"https://orcid.org/0009-0000-1835-9271"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongjiang He","raw_affiliation_strings":["China Telecom Corporation Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"China Telecom Corporation Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373511","display_name":"Yongxiang Li","orcid":"https://orcid.org/0000-0003-0618-6857"},"institutions":[{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]},{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxiang Li","raw_affiliation_strings":["China Telecom Corporation Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"China Telecom Corporation Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407035","display_name":"Chao Wang","orcid":"https://orcid.org/0000-0002-7427-793X"},"institutions":[{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]},{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Wang","raw_affiliation_strings":["China Telecom Corporation Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"China Telecom Corporation Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087486098","display_name":"Shuangyong Song","orcid":"https://orcid.org/0000-0001-7465-1082"},"institutions":[{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]},{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangyong Song","raw_affiliation_strings":["China Telecom Corporation Ltd.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"China Telecom Corporation Ltd.,Beijing,China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100380108"],"corresponding_institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"],"apc_list":null,"apc_paid":null,"fwci":0.3637,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66538794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9991999864578247,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9975000023841858,"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":0.9951000213623047,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dialog-box","display_name":"Dialog box","score":0.7584512233734131},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7572630643844604},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.621036946773529},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.5904568433761597},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5409257411956787},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5043615102767944},{"id":"https://openalex.org/keywords/diversity","display_name":"Diversity (politics)","score":0.4293272793292999},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3314664661884308},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3058963418006897},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2020626664161682},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.11008471250534058},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.09993931651115417},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09772175550460815},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09707000851631165},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.06772813200950623}],"concepts":[{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.7584512233734131},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7572630643844604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.621036946773529},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.5904568433761597},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5409257411956787},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5043615102767944},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.4293272793292999},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3314664661884308},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3058963418006897},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2020626664161682},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.11008471250534058},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.09993931651115417},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09772175550460815},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09707000851631165},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.06772813200950623},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn60899.2024.10651377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1600402929","https://openalex.org/W2101105183","https://openalex.org/W2473930607","https://openalex.org/W2600463316","https://openalex.org/W2945472816","https://openalex.org/W2963072899","https://openalex.org/W2963588172","https://openalex.org/W2971296908","https://openalex.org/W3035542229","https://openalex.org/W3035576098","https://openalex.org/W3043271475","https://openalex.org/W3091123787","https://openalex.org/W3100152912","https://openalex.org/W3102854726","https://openalex.org/W3156627357","https://openalex.org/W3156636935","https://openalex.org/W3174828871","https://openalex.org/W3200693755","https://openalex.org/W3214945533","https://openalex.org/W4205340316","https://openalex.org/W4307823382"],"related_works":["https://openalex.org/W2098987383","https://openalex.org/W2417260800","https://openalex.org/W1596203174","https://openalex.org/W2117933979","https://openalex.org/W2283130723","https://openalex.org/W103938586","https://openalex.org/W2104718772","https://openalex.org/W4233992201","https://openalex.org/W2292950558","https://openalex.org/W2368721880"],"abstract_inverted_index":{"In":[0],"our":[1,113],"dynamic":[2],"world":[3],"where":[4],"data":[5,75],"arrives":[6],"in":[7,30,119],"a":[8,67,100],"continuous":[9],"stream,":[10],"continual":[11,31,62,120],"learning":[12,32,63],"enables":[13],"us":[14],"to":[15,23,43,77,91],"incrementally":[16],"add":[17],"new":[18,53],"tasks/domains":[19,49],"without":[20],"the":[21,39,61,93,117],"need":[22],"retrain":[24],"from":[25,46],"scratch.":[26],"A":[27],"major":[28],"challenge":[29],"of":[33,41,95],"language":[34],"model":[35,79],"is":[36],"catastrophic":[37],"forgetting,":[38],"tendency":[40],"models":[42],"forget":[44],"knowledge":[45],"previously":[47],"trained":[48],"when":[50],"training":[51],"on":[52,81,99],"ones.":[54],"This":[55],"paper":[56],"studies":[57],"dialog":[58,103],"generation":[59],"under":[60],"setting.":[64],"We":[65],"propose":[66],"novel":[68],"method":[69],"that":[70,112],"1)":[71],"uses":[72],"Text-Mixup":[73],"as":[74],"augmentation":[76],"avoid":[78],"overfitting":[80],"replay":[82],"memory":[83],"and":[84,105],"2)":[85],"leverages":[86],"Batch-Nuclear":[87],"Norm":[88],"Maximization":[89],"(BNNM)":[90],"alleviate":[92],"problem":[94],"mode":[96],"collapse.":[97],"Experiments":[98],"37-domain":[101],"task-oriented":[102],"dataset":[104],"DailyDialog":[106],"(a":[107],"10-domain":[108],"chitchat":[109],"dataset)":[110],"demonstrate":[111],"proposed":[114],"approach":[115],"outperforms":[116],"state-of-the-art":[118],"learning.":[121]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
