{"id":"https://openalex.org/W7164385769","doi":"https://doi.org/10.48550/arxiv.2606.11786","title":"Lius: Translation Model Based Instructional Lingustic Using Continual Instruction Tuning In Kupang Malay","display_name":"Lius: Translation Model Based Instructional Lingustic Using Continual Instruction Tuning In Kupang Malay","publication_year":2026,"publication_date":"2026-06-10","ids":{"openalex":"https://openalex.org/W7164385769","doi":"https://doi.org/10.48550/arxiv.2606.11786"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.11786","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11786","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.11786","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093210038","display_name":"Joanito Agili Lopo","orcid":"https://orcid.org/0009-0001-3183-7132"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lopo, Joanito Agili","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048067169","display_name":"Y K Sari","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sari, Yunita","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5030456549","display_name":"Guntur Budi Herwanto","orcid":"https://orcid.org/0000-0003-0250-6884"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Herwanto, Guntur Budi","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":false,"cited_by_count":0,"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":0.44269999861717224,"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":0.44269999861717224,"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":0.09679999947547913,"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":0.06849999725818634,"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/malay","display_name":"Malay","score":0.694599986076355},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6233999729156494},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6032000184059143},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5723000168800354},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.4717999994754791},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4706999957561493},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.39309999346733093},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.3497999906539917}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8027999997138977},{"id":"https://openalex.org/C2776938241","wikidata":"https://www.wikidata.org/wiki/Q9237","display_name":"Malay","level":2,"score":0.694599986076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6330999732017517},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6233999729156494},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6119999885559082},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6032000184059143},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5723000168800354},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.4717999994754791},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4706999957561493},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36059999465942383},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C148526163","wikidata":"https://www.wikidata.org/wiki/Q6723733","display_name":"Machine translation software usability","level":4,"score":0.3481999933719635},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.298799991607666},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C24687705","wikidata":"https://www.wikidata.org/wiki/Q3753284","display_name":"Example-based machine translation","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C2986862884","wikidata":"https://www.wikidata.org/wiki/Q7553","display_name":"Language translation","level":3,"score":0.2831999957561493},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.11786","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11786","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.11786","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.11786","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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6660630106925964,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"offer":[4],"new":[5],"potential":[6,110],"for":[7,27],"translation":[8],"tasks":[9],"but":[10],"often":[11],"experience":[12],"performance":[13],"degradation":[14],"when":[15],"handling":[16],"low-resource":[17,32,123],"languages.":[18],"To":[19],"address":[20],"this":[21],"limitation,":[22],"we":[23],"propose":[24],"an":[25],"approach":[26,37,113],"fine-tuning":[28],"LLMs":[29],"on":[30,102,118],"a":[31,40,52,61],"language,":[33],"Kupang":[34],"Malay.":[35],"Our":[36],"involves":[38],"designing":[39],"set":[41],"of":[42,111],"instructions":[43],"by":[44,84,99],"leveraging":[45],"explicit":[46],"lexical":[47],"and":[48,55,88,95],"semantic":[49],"features":[50],"from":[51],"bilingual":[53],"dictionary,":[54],"introducing":[56],"Continual":[57],"Instruction":[58],"Tuning":[59],"(CIT),":[60],"training":[62],"paradigm":[63],"that":[64,72],"enables":[65],"iterative":[66],"instruction-based":[67],"training.":[68],"Experimental":[69],"results":[70],"demonstrate":[71],"our":[73,112],"model,":[74],"named":[75],"Lius,":[76],"yields":[77],"notable":[78],"improvements":[79],"over":[80],"standard":[81],"instruction-tuned":[82],"models":[83,98],"outperforming":[85],"4-6":[86],"points,":[87],"surpassing":[89],"both":[90],"Neural":[91],"Machine":[92],"Translation":[93],"(NMT)":[94],"Multilingual":[96],"LLM":[97],"10-13":[100],"points":[101],"several":[103],"evaluation":[104],"metrics.":[105],"These":[106],"findings":[107],"highlight":[108],"the":[109,116],"to":[114],"mitigate":[115],"reliance":[117],"large-scale":[119],"parallel":[120],"data":[121],"in":[122],"language":[124],"translation.":[125]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-12T00:00:00"}