{"id":"https://openalex.org/W4388514360","doi":"https://doi.org/10.48550/arxiv.2311.03672","title":"CBSiMT: Mitigating Hallucination in Simultaneous Machine Translation with Weighted Prefix-to-Prefix Training","display_name":"CBSiMT: Mitigating Hallucination in Simultaneous Machine Translation with Weighted Prefix-to-Prefix Training","publication_year":2023,"publication_date":"2023-11-07","ids":{"openalex":"https://openalex.org/W4388514360","doi":"https://doi.org/10.48550/arxiv.2311.03672"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2311.03672","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.03672","pdf_url":"https://arxiv.org/pdf/2311.03672","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2311.03672","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019494082","display_name":"Mengge Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Mengge","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444409","display_name":"Wen Zhang","orcid":"https://orcid.org/0000-0002-8934-3346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100331094","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0002-9851-6376"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051919727","display_name":"Yanzhi Tian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tian, Yanzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101786500","display_name":"Yuhang Guo","orcid":"https://orcid.org/0000-0001-5771-0458"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Yuhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051287176","display_name":"Jian Luan","orcid":"https://orcid.org/0000-0002-3851-0829"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luan, Jian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104189020","display_name":"Bin Wang","orcid":"https://orcid.org/0009-0007-3155-3790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Bin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5059533290","display_name":"Shuoying Chen","orcid":"https://orcid.org/0009-0006-6947-0053"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Shuoying","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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/T13629","display_name":"Text Readability and Simplification","score":0.9937000274658203,"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/prefix","display_name":"Prefix","score":0.9076857566833496},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.795874297618866},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.7781610488891602},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.700599193572998},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6467396020889282},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.5288287997245789},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4692428410053253},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.466980904340744},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4609774351119995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4487975835800171},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3483850955963135},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14760810136795044}],"concepts":[{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.9076857566833496},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.795874297618866},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.7781610488891602},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.700599193572998},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6467396020889282},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.5288287997245789},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4692428410053253},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.466980904340744},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4609774351119995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4487975835800171},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3483850955963135},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14760810136795044},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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},{"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":"pmh:oai:arXiv.org:2311.03672","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.03672","pdf_url":"https://arxiv.org/pdf/2311.03672","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2311.03672","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2311.03672","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2311.03672","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2311.03672","pdf_url":"https://arxiv.org/pdf/2311.03672","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388514360.pdf","grobid_xml":"https://content.openalex.org/works/W4388514360.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2142481367","https://openalex.org/W3196321793","https://openalex.org/W3080705045","https://openalex.org/W2385527937","https://openalex.org/W2005880840","https://openalex.org/W2949968076","https://openalex.org/W2935811960","https://openalex.org/W2969407538","https://openalex.org/W2917049097","https://openalex.org/W4389115113"],"abstract_inverted_index":{"Simultaneous":[0,103],"machine":[1],"translation":[2,11,90,193],"(SiMT)":[3],"is":[4,17,21],"a":[5,34,101],"challenging":[6],"task":[7],"that":[8,62,76,187],"requires":[9],"starting":[10],"before":[12],"the":[13,41,81,88,139,145,148,153,158,163,174],"full":[14],"source":[15,36,66,82,94],"sentence":[16,166],"available.":[18],"Prefix-to-prefix":[19],"framework":[20],"often":[22],"applied":[23],"to":[24,28,40,65,112,161,201],"SiMT,":[25],"which":[26,108],"learns":[27],"predict":[29],"target":[30,60,74,150],"tokens":[31,75,115,151],"using":[32,152],"only":[33,72],"partial":[35],"prefix.":[37],"However,":[38],"due":[39],"word":[42,170],"order":[43,171],"difference":[44],"between":[45],"languages,":[46],"misaligned":[47],"prefix":[48],"pairs":[49,167],"would":[50],"make":[51],"SiMT":[52,184],"models":[53],"suffer":[54],"from":[55],"serious":[56,169],"hallucination":[57,114],"problems,":[58],"i.e.":[59],"outputs":[61],"are":[63,77,130],"unfaithful":[64],"inputs.":[67],"Such":[68],"problems":[69],"can":[70,190],"not":[71,78],"produce":[73],"supported":[79],"by":[80,91],"prefix,":[83],"but":[84],"also":[85],"hinder":[86],"generating":[87],"correct":[89],"receiving":[92],"more":[93],"words.":[95],"In":[96],"this":[97],"work,":[98],"we":[99],"propose":[100],"Confidence-Based":[102],"Machine":[104],"Translation":[105],"(CBSiMT)":[106],"framework,":[107],"uses":[109],"model":[110,134],"confidence":[111,135],"perceive":[113],"and":[116,127,136,156,181],"mitigates":[117],"their":[118],"negative":[119],"impact":[120],"with":[121,168,199],"weighted":[122],"prefix-to-prefix":[123],"training.":[124],"Specifically,":[125],"token-level":[126,154],"sentence-level":[128,159],"weights":[129],"calculated":[131],"based":[132],"on":[133,138,173,178],"acted":[137],"loss":[140],"function.":[141],"We":[142],"explicitly":[143],"quantify":[144],"faithfulness":[146],"of":[147,165],"generated":[149],"weight,":[155],"employ":[157],"weight":[160],"alleviate":[162],"disturbance":[164],"differences":[172],"model.":[175],"Experimental":[176],"results":[177],"MuST-C":[179],"English-to-Chinese":[180],"WMT15":[182],"German-to-English":[183],"tasks":[185],"demonstrate":[186],"our":[188],"method":[189],"consistently":[191],"improve":[192],"quality":[194],"at":[195,206],"most":[196],"latency":[197],"regimes,":[198],"up":[200],"2":[202],"BLEU":[203],"scores":[204],"improvement":[205],"low":[207],"latency.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2023-11-09T00:00:00"}
