{"id":"https://openalex.org/W2474396346","doi":"https://doi.org/10.18653/v1/k16-1021","title":"Exploring Prediction Uncertainty in Machine Translation Quality Estimation","display_name":"Exploring Prediction Uncertainty in Machine Translation Quality Estimation","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2474396346","doi":"https://doi.org/10.18653/v1/k16-1021","mag":"2474396346"},"language":"en","primary_location":{"id":"doi:10.18653/v1/k16-1021","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k16-1021","pdf_url":"https://www.aclweb.org/anthology/K16-1021.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 20th SIGNLL Conference on Computational Natural Language Learning","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/K16-1021.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026654079","display_name":"Daniel Beck","orcid":"https://orcid.org/0000-0001-9560-2773"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Daniel Beck","raw_affiliation_strings":["University of Sheffield, Sheffield, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of Sheffield, Sheffield, United Kingdom","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053217291","display_name":"Lucia Specia","orcid":"https://orcid.org/0000-0002-5495-3128"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lucia Specia","raw_affiliation_strings":["University of Sheffield, Sheffield, United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of Sheffield, Sheffield, United Kingdom","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078530959","display_name":"Trevor Cohn","orcid":"https://orcid.org/0000-0003-4363-1673"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Trevor Cohn","raw_affiliation_strings":["Computing and Information Systems University of Melbourne, Australia","University of Melbourne, Melbourne, Australia"],"affiliations":[{"raw_affiliation_string":"Computing and Information Systems University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026654079"],"corresponding_institution_ids":["https://openalex.org/I91136226"],"apc_list":null,"apc_paid":null,"fwci":0.4417,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.78844806,"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":"208","last_page":"218"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9983999729156494,"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":0.9983999729156494,"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":0.9980999827384949,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.995199978351593,"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/computer-science","display_name":"Computer science","score":0.7832534909248352},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.7010607123374939},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6980633735656738},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6294910311698914},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.6224293112754822},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.5972521305084229},{"id":"https://openalex.org/keywords/point-estimation","display_name":"Point estimation","score":0.5725936889648438},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.552460253238678},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5045269727706909},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5004780292510986},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48837369680404663},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.4784162640571594},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4633029103279114},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.44247251749038696},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4390679597854614},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4325448274612427},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.23821017146110535},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15791428089141846},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11756321787834167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7832534909248352},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.7010607123374939},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6980633735656738},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6294910311698914},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.6224293112754822},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.5972521305084229},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.5725936889648438},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.552460253238678},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5045269727706909},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5004780292510986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48837369680404663},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.4784162640571594},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4633029103279114},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.44247251749038696},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4390679597854614},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4325448274612427},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.23821017146110535},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15791428089141846},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11756321787834167},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"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/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.18653/v1/k16-1021","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k16-1021","pdf_url":"https://www.aclweb.org/anthology/K16-1021.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 20th SIGNLL Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1606.09600","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1606.09600","pdf_url":"https://arxiv.org/pdf/1606.09600","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":null,"raw_type":"text"},{"id":"mag:2474396346","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1606.09600.pdf","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1606.09600","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1606.09600","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"}],"best_oa_location":{"id":"doi:10.18653/v1/k16-1021","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/k16-1021","pdf_url":"https://www.aclweb.org/anthology/K16-1021.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 20th SIGNLL Conference on Computational Natural Language Learning","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1904485870","display_name":null,"funder_award_id":"CNPq/Brazil","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G3601516360","display_name":null,"funder_award_id":"Brazil","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G5079005330","display_name":null,"funder_award_id":"support","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2474396346.pdf","grobid_xml":"https://content.openalex.org/works/W2474396346.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1527525292","https://openalex.org/W1682639223","https://openalex.org/W1746819321","https://openalex.org/W1783061888","https://openalex.org/W1933798900","https://openalex.org/W2018770010","https://openalex.org/W2042590947","https://openalex.org/W2061885628","https://openalex.org/W2079521622","https://openalex.org/W2108324828","https://openalex.org/W2133675239","https://openalex.org/W2134477639","https://openalex.org/W2137018331","https://openalex.org/W2149327368","https://openalex.org/W2150582689","https://openalex.org/W2158471180","https://openalex.org/W2160001241","https://openalex.org/W2171305756","https://openalex.org/W2186839874","https://openalex.org/W2251150371","https://openalex.org/W2251311344","https://openalex.org/W2251557434","https://openalex.org/W2252083640","https://openalex.org/W2950177356","https://openalex.org/W2952677397","https://openalex.org/W3044695148"],"related_works":["https://openalex.org/W3194962404","https://openalex.org/W3177536598","https://openalex.org/W3162640085","https://openalex.org/W2989902657","https://openalex.org/W3178722732","https://openalex.org/W2887922452","https://openalex.org/W2328068301","https://openalex.org/W2998618342","https://openalex.org/W2042647242","https://openalex.org/W2593353420","https://openalex.org/W3118447680","https://openalex.org/W2064695413","https://openalex.org/W3119028141","https://openalex.org/W2559905398","https://openalex.org/W2901713869","https://openalex.org/W3198433605","https://openalex.org/W2924065238","https://openalex.org/W2567388360","https://openalex.org/W3127266258","https://openalex.org/W3015775158"],"abstract_inverted_index":{"Machine":[0],"Translation":[1],"Quality":[2,60],"Estimation":[3,61],"is":[4],"a":[5,28],"notoriously":[6],"difficult":[7],"task,":[8],"which":[9,47,94],"lessens":[10],"its":[11],"usefulness":[12],"in":[13,34,41,71,89,100],"real-world":[14],"translation":[15,101],"environments.":[16],"Such":[17],"scenarios":[18],"can":[19,63,86],"be":[20,87],"improved":[21],"if":[22],"quality":[23],"predictions":[24],"are":[25,37],"accompanied":[26],"by":[27],"measure":[29],"of":[30,43,73],"uncertainty.":[31],"However,":[32],"models":[33],"this":[35,83],"task":[36],"traditionally":[38],"evaluated":[39],"only":[40],"terms":[42,72],"point":[44],"estimate":[45],"metrics,":[46],"do":[48],"not":[49],"take":[50],"prediction":[51],"uncertainty":[52,66],"into":[53],"account.":[54],"We":[55,79],"investigate":[56],"probabilistic":[57],"methods":[58],"for":[59],"that":[62],"provide":[64],"well-calibrated":[65],"estimates":[67],"and":[68],"evaluate":[69],"them":[70],"their":[74],"full":[75],"posterior":[76,84],"predictive":[77],"distributions.":[78],"also":[80],"show":[81],"how":[82],"information":[85],"useful":[88],"an":[90],"asymmetric":[91],"risk":[92],"scenario,":[93],"aims":[95],"to":[96],"capture":[97],"typical":[98],"situations":[99],"workflows.":[102]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
