{"id":"https://openalex.org/W3119269421","doi":"https://doi.org/10.18653/v1/2020.wmt-1.141","title":"Incorporating Terminology Constraints in Automatic Post-Editing","display_name":"Incorporating Terminology Constraints in Automatic Post-Editing","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3119269421","doi":"https://doi.org/10.18653/v1/2020.wmt-1.141","mag":"3119269421"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2020.wmt-1.141","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.wmt-1.141","pdf_url":"https://aclanthology.org/2020.wmt-1.141.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 Fifth Conference on Machine Translation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2020.wmt-1.141.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049780941","display_name":"David Wan","orcid":"https://orcid.org/0000-0002-1969-1986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Wan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006374446","display_name":"Chris Kedzie","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chris Kedzie","raw_affiliation_strings":["Columbia University, New York, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, United States","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074277807","display_name":"Faisal Ladhak","orcid":"https://orcid.org/0009-0009-5730-3866"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Faisal Ladhak","raw_affiliation_strings":["Columbia University, New York, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, United States","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078390032","display_name":"Marine Carpuat","orcid":"https://orcid.org/0000-0003-1693-0782"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marine Carpuat","raw_affiliation_strings":["University of Maryland, College Park, College Park, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park, College Park, United States","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109565051","display_name":"Kathleen McKeown","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kathleen McKeown","raw_affiliation_strings":["Columbia University, New York, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York, United States","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1193","last_page":"1204"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9812999963760376,"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/terminology","display_name":"Terminology","score":0.8430295586585999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8126343488693237},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7007431983947754},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6484156847000122},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6439868211746216},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.5346300601959229},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.527579665184021},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5145718455314636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37788182497024536},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.12487617135047913},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.09600237011909485},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06632661819458008}],"concepts":[{"id":"https://openalex.org/C547195049","wikidata":"https://www.wikidata.org/wiki/Q1725664","display_name":"Terminology","level":2,"score":0.8430295586585999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8126343488693237},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7007431983947754},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6484156847000122},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6439868211746216},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.5346300601959229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.527579665184021},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5145718455314636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37788182497024536},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.12487617135047913},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.09600237011909485},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06632661819458008},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/2020.wmt-1.141","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.wmt-1.141","pdf_url":"https://aclanthology.org/2020.wmt-1.141.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 Fifth Conference on Machine Translation","raw_type":"proceedings-article"},{"id":"mag:3119269421","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2010.09608","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":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"doi:10.18653/v1/2020.wmt-1.141","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.wmt-1.141","pdf_url":"https://aclanthology.org/2020.wmt-1.141.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 Fifth Conference on Machine Translation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7904372578","display_name":null,"funder_award_id":"FA8650-17-C-9117","funder_id":"https://openalex.org/F4320333051","funder_display_name":"Intelligence Advanced Research Projects Activity"}],"funders":[{"id":"https://openalex.org/F4320312530","display_name":"Office of the Director of National Intelligence","ror":"https://ror.org/01v3fsc55"},{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3119269421.pdf","grobid_xml":"https://content.openalex.org/works/W3119269421.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W2101105183","https://openalex.org/W2141971526","https://openalex.org/W2149327368","https://openalex.org/W2933138175","https://openalex.org/W2951770285","https://openalex.org/W2962678612","https://openalex.org/W2962784628","https://openalex.org/W2962826395","https://openalex.org/W2963352809","https://openalex.org/W2963403868","https://openalex.org/W2963816901","https://openalex.org/W2964029788","https://openalex.org/W2970326214","https://openalex.org/W2970461932","https://openalex.org/W2970871182","https://openalex.org/W2971167892","https://openalex.org/W3006354580","https://openalex.org/W3006530332","https://openalex.org/W3035540807"],"related_works":["https://openalex.org/W3176785110","https://openalex.org/W3200875022","https://openalex.org/W3197941676","https://openalex.org/W1981372412","https://openalex.org/W2251556439","https://openalex.org/W2127191681","https://openalex.org/W2394897527","https://openalex.org/W2034639451","https://openalex.org/W2182281881","https://openalex.org/W2406480483","https://openalex.org/W162364964","https://openalex.org/W3171126283","https://openalex.org/W2970223278","https://openalex.org/W2787770455","https://openalex.org/W2165666205","https://openalex.org/W2100565866","https://openalex.org/W2103222490","https://openalex.org/W2951634843","https://openalex.org/W2900556903","https://openalex.org/W2886964929"],"abstract_inverted_index":{"Users":[0],"of":[1,11,58,60,85],"machine":[2],"translation":[3,66],"(MT)":[4],"may":[5],"want":[6],"to":[7,73,82,96,109],"ensure":[8,30],"the":[9,36,61,86],"use":[10],"specific":[12],"lexical":[13],"terminologies.While":[14],"there":[15],"exist":[16],"techniques":[17],"for":[18,24,48],"incorporating":[19],"terminology":[20],"constraints":[21,98],"during":[22],"inference":[23],"MT,":[25],"current":[26],"APE":[27],"approaches":[28],"cannot":[29],"that":[31,53,90,107],"they":[32],"will":[33],"appear":[34],"in":[35],"final":[37],"translation.In":[38],"this":[39],"paper,":[40],"we":[41,88],"present":[42],"both":[43],"autoregressive":[44],"and":[45,63,100,112],"non-autoregressive":[46],"models":[47,92],"lexically":[49,74],"constrained":[50,75],"APE,":[51],"demonstrating":[52],"our":[54,78,91],"approach":[55,79],"enables":[56],"preservation":[57,84],"95%":[59],"terminologies":[62],"also":[64],"improves":[65],"quality":[67],"on":[68],"English-German":[69],"benchmarks.Even":[70],"when":[71],"applied":[72],"MT":[76],"output,":[77],"is":[80],"able":[81],"improve":[83],"terminologies.However,":[87],"show":[89],"do":[93],"not":[94],"learn":[95],"copy":[97],"systematically":[99],"suggest":[101],"a":[102],"simple":[103],"data":[104],"augmentation":[105],"technique":[106],"leads":[108],"improved":[110],"performance":[111],"robustness.":[113]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-01-18T00:00:00"}