{"id":"https://openalex.org/W3025877323","doi":"https://doi.org/10.18653/v1/2020.acl-main.138","title":"NAT: Noise-Aware Training for Robust Neural Sequence Labeling","display_name":"NAT: Noise-Aware Training for Robust Neural Sequence Labeling","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3025877323","doi":"https://doi.org/10.18653/v1/2020.acl-main.138","mag":"3025877323"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2020.acl-main.138","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.acl-main.138","pdf_url":"https://www.aclweb.org/anthology/2020.acl-main.138.pdf","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 58th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/2020.acl-main.138.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084431990","display_name":"Marcin Namys\u0142","orcid":"https://orcid.org/0000-0001-7066-1726"},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]},{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Marcin Namysl","raw_affiliation_strings":["Autonomous Intelligent Systems, Computer Science Institute VI, University of Bonn, Germany","Fraunhofer IAIS, Sankt Augustin, Germany"],"affiliations":[{"raw_affiliation_string":"Autonomous Intelligent Systems, Computer Science Institute VI, University of Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"Fraunhofer IAIS, Sankt Augustin, Germany","institution_ids":["https://openalex.org/I4210144576"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027761977","display_name":"Sven Behnke","orcid":"https://orcid.org/0000-0002-5040-7525"},"institutions":[{"id":"https://openalex.org/I4210144576","display_name":"Fraunhofer Institute for Intelligent Analysis and Information Systems","ror":"https://ror.org/04nc32781","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210144576","https://openalex.org/I4923324"]},{"id":"https://openalex.org/I135140700","display_name":"University of Bonn","ror":"https://ror.org/041nas322","country_code":"DE","type":"education","lineage":["https://openalex.org/I135140700"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sven Behnke","raw_affiliation_strings":["Autonomous Intelligent Systems, Computer Science Institute VI, University of Bonn, Germany","Fraunhofer IAIS, Sankt Augustin, Germany"],"affiliations":[{"raw_affiliation_string":"Autonomous Intelligent Systems, Computer Science Institute VI, University of Bonn, Germany","institution_ids":["https://openalex.org/I135140700"]},{"raw_affiliation_string":"Fraunhofer IAIS, Sankt Augustin, Germany","institution_ids":["https://openalex.org/I4210144576"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103573586","display_name":"Joachim K\u00f6hler","orcid":null},"institutions":[{"id":"https://openalex.org/I4923324","display_name":"Fraunhofer Society","ror":"https://ror.org/05hkkdn48","country_code":"DE","type":"funder","lineage":["https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Joachim K\u00f6hler","raw_affiliation_strings":["Fraunhofer Society"],"affiliations":[{"raw_affiliation_string":"Fraunhofer Society","institution_ids":["https://openalex.org/I4923324"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084431990"],"corresponding_institution_ids":["https://openalex.org/I135140700","https://openalex.org/I4210144576"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05102995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1501","last_page":"1517"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9932000041007996,"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":0.7791252732276917},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7532610893249512},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"Sequence labeling","score":0.5916732549667358},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5679590702056885},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5663310289382935},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.49154338240623474},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.48153048753738403},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43259984254837036},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.39520302414894104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36308586597442627},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3274189829826355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7791252732276917},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7532610893249512},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.5916732549667358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5679590702056885},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5663310289382935},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.49154338240623474},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.48153048753738403},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43259984254837036},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39520302414894104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36308586597442627},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3274189829826355},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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}],"mesh":[],"locations_count":9,"locations":[{"id":"doi:10.18653/v1/2020.acl-main.138","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.acl-main.138","pdf_url":"https://www.aclweb.org/anthology/2020.acl-main.138.pdf","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 58th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2005.07162","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2005.07162","pdf_url":"https://arxiv.org/pdf/2005.07162","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:fraunhofer.de:N-596978","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-596978.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IAIS","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/408464","is_oa":true,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/408464","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/501298","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/501298","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/502449","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/502449","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},{"id":"doi:10.48550/arxiv.2005.07162","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2005.07162","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.24406/publica-fhg-408464","is_oa":true,"landing_page_url":"https://doi.org/10.24406/publica-fhg-408464","pdf_url":null,"source":{"id":"https://openalex.org/S7407052912","display_name":"Fraunhofer-Gesellschaft zur F\u00f6rderung der angewandten Forschung e.V","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"},{"id":"mag:3025877323","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"doi:10.18653/v1/2020.acl-main.138","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.acl-main.138","pdf_url":"https://www.aclweb.org/anthology/2020.acl-main.138.pdf","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 58th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3025877323.pdf","grobid_xml":"https://content.openalex.org/works/W3025877323.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1647671624","https://openalex.org/W1940872118","https://openalex.org/W1968290777","https://openalex.org/W2001642682","https://openalex.org/W2004763266","https://openalex.org/W2057900969","https://openalex.org/W2095705004","https://openalex.org/W2101793424","https://openalex.org/W2125825154","https://openalex.org/W2138738738","https://openalex.org/W2144578941","https://openalex.org/W2147880316","https://openalex.org/W2163605009","https://openalex.org/W2168322422","https://openalex.org/W2250539671","https://openalex.org/W2251160521","https://openalex.org/W2296283641","https://openalex.org/W2342045095","https://openalex.org/W2406932913","https://openalex.org/W2559662148","https://openalex.org/W2575782020","https://openalex.org/W2579840722","https://openalex.org/W2741908291","https://openalex.org/W2753681151","https://openalex.org/W2756610685","https://openalex.org/W2786672397","https://openalex.org/W2799194071","https://openalex.org/W2880875857","https://openalex.org/W2945808722","https://openalex.org/W2962718684","https://openalex.org/W2962739339","https://openalex.org/W2962818281","https://openalex.org/W2963207607","https://openalex.org/W2963213832","https://openalex.org/W2963341956","https://openalex.org/W2963625095","https://openalex.org/W2963661177","https://openalex.org/W2963823140","https://openalex.org/W2963997908","https://openalex.org/W2964048171","https://openalex.org/W2964091575","https://openalex.org/W2964153729","https://openalex.org/W2964185534","https://openalex.org/W2971091580","https://openalex.org/W2984051011","https://openalex.org/W3003543339","https://openalex.org/W3093419064"],"related_works":["https://openalex.org/W3176905299","https://openalex.org/W2809951251","https://openalex.org/W2979707486","https://openalex.org/W2606308499","https://openalex.org/W3174485549","https://openalex.org/W3096157982","https://openalex.org/W3207337382","https://openalex.org/W2121056381","https://openalex.org/W3134061603","https://openalex.org/W3105011493","https://openalex.org/W3200556739","https://openalex.org/W2974413178","https://openalex.org/W3040553166","https://openalex.org/W3164866731","https://openalex.org/W2774079475","https://openalex.org/W3194859544","https://openalex.org/W2963509340","https://openalex.org/W2955385886","https://openalex.org/W3201674335","https://openalex.org/W3154887629"],"abstract_inverted_index":{"Sequence":[0],"labeling":[1,36,59,140],"systems":[2,17],"should":[3],"perform":[4],"reliably":[5],"not":[6],"only":[7],"under":[8],"ideal":[9],"conditions":[10],"but":[11],"also":[12],"with":[13,115],"corrupted":[14],"inputs-as":[15],"these":[16],"often":[18],"process":[19,46],"user-generated":[20],"text":[21],"or":[22],"follow":[23],"an":[24,43],"errorprone":[25],"upstream":[26],"component.":[27],"To":[28],"this":[29],"end,":[30],"we":[31,105],"formulate":[32],"the":[33,39,86,108,145,157],"noisy":[34,78],"sequence":[35,58,139],"problem,":[37],"where":[38],"input":[40],"may":[41],"undergo":[42],"unknown":[44],"noising":[45],"and":[47,77,111,119,125,152],"propose":[48],"two":[49],"Noise-Aware":[50],"Training":[51],"(NAT)":[52],"objectives":[53],"that":[54,132],"improve":[55],"robustness":[56,136],"of":[57,75,137],"performed":[60],"on":[61,123,144],"perturbed":[62,114],"input:":[63],"Our":[64],"data":[65,110,153],"augmentation":[66],"method":[67],"trains":[68],"a":[69,73,90,96],"neural":[70],"model":[71,87,99],"using":[72],"mixture":[74],"clean":[76],"samples,":[79],"whereas":[80],"our":[81,150],"stability":[82],"training":[83,101],"algorithm":[84],"encourages":[85],"to":[88],"create":[89],"noise-invariant":[91],"latent":[92],"representation.":[93],"We":[94,148],"employ":[95],"vanilla":[97],"noise":[98],"at":[100],"time.":[102],"For":[103],"evaluation,":[104],"use":[106],"both":[107],"original":[109,146],"its":[112],"variants":[113],"real":[116],"OCR":[117],"errors":[118],"misspellings.":[120],"Extensive":[121],"experiments":[122],"English":[124],"German":[126],"named":[127],"entity":[128],"recognition":[129],"benchmarks":[130],"confirmed":[131],"NAT":[133],"consistently":[134],"improved":[135],"popular":[138],"models,":[141],"preserving":[142],"accuracy":[143],"input.":[147],"make":[149],"code":[151],"publicly":[154],"available":[155],"for":[156],"research":[158],"community.":[159]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
