{"id":"https://openalex.org/W4389518809","doi":"https://doi.org/10.18653/v1/2023.wmt-1.59","title":"Tokengram_F, a Fast and Accurate Token-based chrF++ Derivative","display_name":"Tokengram_F, a Fast and Accurate Token-based chrF++ Derivative","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4389518809","doi":"https://doi.org/10.18653/v1/2023.wmt-1.59"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2023.wmt-1.59","doi":"https://doi.org/10.18653/v1/2023.wmt-1.59","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.wmt-1.59","pdf_url":"https://aclanthology.org/2023.wmt-1.59.pdf","source":{"id":"https://openalex.org/S7407087242","display_name":"Conference on Machine Translation (WMT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 Eighth Conference on Machine Translation","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2023.wmt-1.59.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093457082","display_name":"S\u00f6ren Dreano","orcid":"https://orcid.org/0009-0007-1087-2274","observed_orcids":["https://orcid.org/0009-0007-1087-2274"]},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"S\u00f6ren Dreano","raw_affiliation_strings":["ML-Labs Dublin City University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ML-Labs Dublin City University","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040062069","display_name":"Derek Molloy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Derek Molloy","raw_affiliation_strings":["School of Electronic Engineering Dublin City University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering Dublin City University","institution_ids":["https://openalex.org/I42934936"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109031157","display_name":"Noel A. Murphy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I42934936","display_name":"Dublin City University","ror":"https://ror.org/04a1a1e81","country_code":"IE","type":"education","lineage":["https://openalex.org/I42934936"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Noel Murphy","raw_affiliation_strings":["School of Electronic Engineering Dublin City University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering Dublin City University","institution_ids":["https://openalex.org/I42934936"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I42934936"],"apc_list":null,"apc_paid":null,"fwci":0.3314,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53253921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"730","last_page":"737"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9965999722480774,"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":0.9965999722480774,"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":0.0012000000569969416,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.0005000000237487257,"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/machine-translation-evaluation","display_name":"machine translation evaluation","score":0.9279999732971191},{"id":"https://openalex.org/keywords/chrf","display_name":"chrF","score":0.9120000004768372},{"id":"https://openalex.org/keywords/tokenization","display_name":"tokenization","score":0.7839999794960022},{"id":"https://openalex.org/keywords/f-score","display_name":"F-score","score":0.5270000100135803},{"id":"https://openalex.org/keywords/word-n-grams","display_name":"word n-grams","score":0.699999988079071},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"semantic similarity","score":0.4970000088214874},{"id":"https://openalex.org/keywords/low-resource-languages","display_name":"low-resource languages","score":0.8489999771118164}],"concepts":[{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.6597038507461548},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5607401132583618},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5527089834213257},{"id":"https://openalex.org/C176982825","wikidata":"https://www.wikidata.org/wiki/Q835922","display_name":"Lexical analysis","level":2,"score":0.5424684882164001},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5247131586074829},{"id":"https://openalex.org/C2777549182","wikidata":"https://www.wikidata.org/wiki/Q15117556","display_name":"Abort","level":2,"score":0.4588308036327362},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37725093960762024},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36206430196762085},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29031550884246826},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11990579962730408},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.07750147581100464},{"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2023.wmt-1.59","doi":"https://doi.org/10.18653/v1/2023.wmt-1.59","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.wmt-1.59","pdf_url":"https://aclanthology.org/2023.wmt-1.59.pdf","source":{"id":"https://openalex.org/S7407087242","display_name":"Conference on Machine Translation (WMT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 Eighth Conference on Machine Translation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2023.wmt-1.59","doi":"https://doi.org/10.18653/v1/2023.wmt-1.59","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2023.wmt-1.59","pdf_url":"https://aclanthology.org/2023.wmt-1.59.pdf","source":{"id":"https://openalex.org/S7407087242","display_name":"Conference on Machine Translation (WMT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 Eighth Conference on Machine Translation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320847","display_name":"Science Foundation Ireland","ror":"https://ror.org/0271asj38"},{"id":"https://openalex.org/F4320321532","display_name":"Child Health Research Foundation","ror":"https://ror.org/04eak0r73"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389518809.pdf","grobid_xml":"https://content.openalex.org/works/W4389518809.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W630532510","https://openalex.org/W2101105183","https://openalex.org/W2123301721","https://openalex.org/W2149327368","https://openalex.org/W2250342921","https://openalex.org/W2758950307","https://openalex.org/W2885185669","https://openalex.org/W2897105542","https://openalex.org/W2962784628","https://openalex.org/W3087597081","https://openalex.org/W3119000810","https://openalex.org/W3119878165"],"related_works":["https://openalex.org/W2250342921","https://openalex.org/W4404781841","https://openalex.org/W2085269238","https://openalex.org/W2758950307","https://openalex.org/W7166500791","https://openalex.org/W202394046","https://openalex.org/W2758250240","https://openalex.org/W2251056729","https://openalex.org/W4385570091","https://openalex.org/W3211458864"],"abstract_inverted_index":{"The":[0],"tokengram_F":[1,85,122,159],"metric":[2,58,108,123,160],"presented":[3],"in":[4,49],"this":[5],"paper":[6],"is":[7,54,63,115,139],"a":[8,26,42,72,133,136,147],"novel":[9],"approach":[10],"to":[11,40,51,117,161],"evaluating":[12,30],"machine":[13,31],"translation":[14,32],"that":[15,33,62,114],"has":[16],"been":[17],"submitted":[18],"as":[19,71],"part":[20],"of":[21,36,46,103,146,157],"the":[22,47,91,106,144,155,158],"WMT23":[23],"challenge.It":[24],"offers":[25],"new":[27],"perspective":[28],"on":[29,99],"takes":[34],"advantage":[35],"modern":[37],"tokenization":[38,83],"algorithms":[39],"provide":[41],"more":[43,73,118],"natural":[44],"representation":[45],"language":[48,138,149],"comparison":[50],"word":[52,77],"n-grams.Tokengram_F":[53],"an":[55,100],"F-score-based":[56],"evaluation":[57],"for":[59,135],"Machine":[60],"Translation":[61],"heavily":[64],"inspired":[65],"by":[66,127],"chrF++":[67],"and":[68],"can":[69,150],"act":[70],"accurate":[74],"replacement.By":[75],"replacing":[76],"n-grams":[78,80],"with":[79],"obtained":[81],"from":[82],"algorithms,":[84],"captures":[86],"similarities":[87],"between":[88],"words":[89],"sharing":[90],"same":[92],"semantic":[93],"roots.While":[94],"requiring":[95],"minimal":[96],"training":[97],"based":[98],"open":[101],"corpus":[102],"monolingual":[104],"datasets,":[105],"token-gram_F":[107],"proposed":[109],"still":[110],"retains":[111],"excellent":[112],"performance":[113],"comparable":[116],"computationally":[119],"expensive":[120],"metrics.The":[121],"demonstrates":[124],"its":[125],"versatility":[126],"showing":[128],"satisfactory":[129],"results,":[130],"even":[131],"when":[132],"tokenizer":[134,145],"specific":[137],"not":[140],"available.In":[141],"such":[142],"cases,":[143],"related":[148],"be":[151],"used":[152],"instead,":[153],"highlighting":[154],"adaptability":[156],"less":[162],"commonly-used":[163],"languages.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-12-10T00:00:00"}
