{"id":"https://openalex.org/W4385565476","doi":"https://doi.org/10.1145/3580305.3599864","title":"Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding","display_name":"Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385565476","doi":"https://doi.org/10.1145/3580305.3599864"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599864","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599864","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599864","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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599864","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018990800","display_name":"Haoyu Wang","orcid":"https://orcid.org/0000-0001-7485-6213"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haoyu Wang","raw_affiliation_strings":["Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101752145","display_name":"Yaqing Wang","orcid":"https://orcid.org/0000-0002-1548-0727"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaqing Wang","raw_affiliation_strings":["Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080988180","display_name":"Feijie Wu","orcid":"https://orcid.org/0000-0003-0541-1901"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feijie Wu","raw_affiliation_strings":["Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014632942","display_name":"Hongfei Xue","orcid":"https://orcid.org/0000-0001-9691-9668"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongfei Xue","raw_affiliation_strings":["University at Buffalo, Buffalo, USA"],"affiliations":[{"raw_affiliation_string":"University at Buffalo, Buffalo, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068042288","display_name":"Jing Gao","orcid":"https://orcid.org/0000-0002-1557-7553"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing Gao","raw_affiliation_strings":["Purdue University, West Lafayette, USA"],"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018990800"],"corresponding_institution_ids":["https://openalex.org/I219193219"],"apc_list":null,"apc_paid":null,"fwci":0.1728,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55444125,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"5061","last_page":"5070"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9998000264167786,"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":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.8883841037750244},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7480290532112122},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.7295762300491333},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6598188281059265},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.64280766248703},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6055450439453125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5789692401885986},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.4454449713230133}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8883841037750244},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7480290532112122},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.7295762300491333},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6598188281059265},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.64280766248703},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6055450439453125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5789692401885986},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.4454449713230133},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3580305.3599864","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599864","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599864","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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3580305.3599864","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3580305.3599864","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3580305.3599864","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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G3148748826","display_name":"III: Medium: Collaborative Research: Mining and Leveraging Knowledge Hypercubes for Complex Applications","funder_award_id":"2141037","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4379077367","display_name":null,"funder_award_id":"IIS-1747614","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7238017987","display_name":null,"funder_award_id":"IIS-1747614, IIS-2141037","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8541794061","display_name":"EAGER: Medical Knowledge Graph Construction from Heterogeneous Sources","funder_award_id":"1747614","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385565476.pdf","grobid_xml":"https://content.openalex.org/works/W4385565476.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W2117130368","https://openalex.org/W2250385423","https://openalex.org/W2516255829","https://openalex.org/W2769280657","https://openalex.org/W2963168538","https://openalex.org/W2963729324","https://openalex.org/W3001434439","https://openalex.org/W3080800398","https://openalex.org/W3104723404","https://openalex.org/W3174933223","https://openalex.org/W3210703476","https://openalex.org/W4205918858","https://openalex.org/W4206727248","https://openalex.org/W4211074922","https://openalex.org/W4287889133"],"related_works":["https://openalex.org/W3089357417","https://openalex.org/W4288263119","https://openalex.org/W3015724364","https://openalex.org/W2967994095","https://openalex.org/W4226226396","https://openalex.org/W4285240985","https://openalex.org/W2900126711","https://openalex.org/W760396729","https://openalex.org/W4308854837","https://openalex.org/W3153750606"],"abstract_inverted_index":{"Cross-lingual":[0],"natural":[1],"language":[2,12],"understanding~(NLU)":[3],"aims":[4],"to":[5,17,83,101,116,140,150],"train":[6],"NLU":[7,18,37,106,158],"models":[8,16,38],"on":[9,87,127,155],"a":[10,25],"source":[11,51,129],"and":[13,23,48,52,67,98,130,143],"apply":[14],"the":[15,34,40,59,85],"tasks":[19,122],"in":[20,50],"target":[21,53,131],"languages,":[22],"is":[24,65,138],"fundamental":[26],"task":[27,107],"for":[28,123],"many":[29],"cross-language":[30],"applications.":[31],"Most":[32],"of":[33,42,61],"existing":[35,141,148],"cross-lingual":[36,105,157],"assume":[39],"existence":[41],"parallel":[43,63,89,110],"corpora":[44,64,111],"so":[45],"that":[46],"words":[47],"sentences":[49],"languages":[54],"could":[55,144],"be":[56,145],"aligned.":[57],"However,":[58],"construction":[60],"such":[62],"expensive":[66],"sometimes":[68],"infeasible.":[69],"Motivated":[70],"by":[71],"this":[72,92,103],"challenge,":[73],"recent":[74],"works":[75],"propose":[76,95,115],"data":[77],"augmentation":[78],"or":[79],"adversarial":[80],"training":[81],"methods":[82,149],"reduce":[84],"reliance":[86],"external":[88],"corpora.":[90],"In":[91],"paper,":[93],"we":[94],"an":[96],"orthogonal":[97],"novel":[99],"perspective":[100],"tackle":[102],"challenging":[104,156],"(i.e.,":[108],"when":[109],"are":[112],"unavailable).":[113],"We":[114],"conduct":[117],"multi-task":[118,135],"learning":[119,136],"across":[120],"different":[121],"mutual":[124],"performance":[125,154],"improvement":[126],"both":[128],"languages.":[132],"The":[133],"proposed":[134],"framework":[137],"complementary":[139],"studies":[142],"integrated":[146],"with":[147],"further":[151],"improve":[152],"their":[153],"tasks.":[159]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
