{"id":"https://openalex.org/W7219106926","doi":"https://doi.org/10.48084/etasr.20006","title":"LAASF: A Language-Aware Adaptive Sentiment Framework with Adapter Fusion for Low-Resource Languages","display_name":"LAASF: A Language-Aware Adaptive Sentiment Framework with Adapter Fusion for Low-Resource Languages","publication_year":2026,"publication_date":"2026-10-02","ids":{"openalex":"https://openalex.org/W7219106926","doi":"https://doi.org/10.48084/etasr.20006"},"language":"en","primary_location":{"id":"doi:10.48084/etasr.20006","doi":"https://doi.org/10.48084/etasr.20006","is_oa":true,"landing_page_url":"https://doi.org/10.48084/etasr.20006","pdf_url":"https://www.etasr.com/index.php/ETASR/article/download/20006/7150","source":{"id":"https://openalex.org/S2737646863","display_name":"Engineering Technology & Applied Science Research","issn_l":"1792-8036","issn":["1792-8036","2241-4487"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310318068","host_organization_name":"Engineering, Technology & Applied Science Research","host_organization_lineage":["https://openalex.org/P4310318068"],"host_organization_lineage_names":["Engineering, Technology & Applied Science Research"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering, Technology & Applied Science Research","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.etasr.com/index.php/ETASR/article/download/20006/7150","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017070033","display_name":"D. K. Meghana","orcid":"https://orcid.org/0000-0001-5441-6958","observed_orcids":["https://orcid.org/0000-0001-5441-6958"]},"institutions":[{"id":"https://openalex.org/I53465836","display_name":"Bangalore University","ror":"https://ror.org/050j2vm64","country_code":"IN","type":"education","lineage":["https://openalex.org/I53465836"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"D. K. Meghana","raw_affiliation_strings":["Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India","institution_ids":["https://openalex.org/I53465836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5156330966","display_name":"K. Kiran","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I53465836","display_name":"Bangalore University","ror":"https://ror.org/050j2vm64","country_code":"IN","type":"education","lineage":["https://openalex.org/I53465836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. Kiran","raw_affiliation_strings":["Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India","institution_ids":["https://openalex.org/I53465836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102811419","display_name":"P. Deepa Shenoy","orcid":"https://orcid.org/0000-0003-0113-1419","observed_orcids":["https://orcid.org/0000-0003-0113-1419"]},"institutions":[{"id":"https://openalex.org/I53465836","display_name":"Bangalore University","ror":"https://ror.org/050j2vm64","country_code":"IN","type":"education","lineage":["https://openalex.org/I53465836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"P. Deepa Shenoy","raw_affiliation_strings":["Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India","institution_ids":["https://openalex.org/I53465836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108553239","display_name":"K. R. Venugopal","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I53465836","display_name":"Bangalore University","ror":"https://ror.org/050j2vm64","country_code":"IN","type":"education","lineage":["https://openalex.org/I53465836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. R. Venugopal","raw_affiliation_strings":["Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CSE, University Visvesvaraya College of Engineering, Bangalore University, Bengaluru, Karnataka, India","institution_ids":["https://openalex.org/I53465836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5017070033"],"corresponding_institution_ids":["https://openalex.org/I53465836"],"apc_list":{"value":400,"currency":"EUR","value_usd":431},"apc_paid":{"value":400,"currency":"EUR","value_usd":431},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"5","first_page":"39494","last_page":"39500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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":9.999999747378752e-05,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"sentiment analysis","score":0.9649999737739563},{"id":"https://openalex.org/keywords/low-resource-languages","display_name":"low-resource languages","score":0.9919999837875366},{"id":"https://openalex.org/keywords/kannada","display_name":"Kannada language","score":0.984000027179718},{"id":"https://openalex.org/keywords/code-mixed-text","display_name":"code-mixed text","score":0.8090000152587891},{"id":"https://openalex.org/keywords/cross-lingual-knowledge-transfer","display_name":"cross-lingual knowledge transfer","score":0.8410000205039978},{"id":"https://openalex.org/keywords/multilingual-transformers","display_name":"multilingual transformer models","score":0.7429999709129333},{"id":"https://openalex.org/keywords/muril","display_name":"MuRIL","score":0.847000002861023},{"id":"https://openalex.org/keywords/xlm-r","display_name":"XLM-R","score":0.9879999756813049},{"id":"https://openalex.org/keywords/adaptive-ensemble","display_name":"adaptive ensemble","score":0.8050000071525574},{"id":"https://openalex.org/keywords/domain-robustness","display_name":"domain robustness","score":0.6859999895095825}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7730000019073486},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.6571000218391418},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6312999725341797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5809999704360962},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5546000003814697},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4553000032901764},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4368000030517578},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.42239999771118164},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.388700008392334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36800000071525574},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32089999318122864},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3000999987125397},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.28850001096725464},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.28839999437332153},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.2825999855995178},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C2775953691","wikidata":"https://www.wikidata.org/wiki/Q5013874","display_name":"CRFS","level":3,"score":0.2533000111579895},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48084/etasr.20006","doi":"https://doi.org/10.48084/etasr.20006","is_oa":true,"landing_page_url":"https://doi.org/10.48084/etasr.20006","pdf_url":"https://www.etasr.com/index.php/ETASR/article/download/20006/7150","source":{"id":"https://openalex.org/S2737646863","display_name":"Engineering Technology & Applied Science Research","issn_l":"1792-8036","issn":["1792-8036","2241-4487"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310318068","host_organization_name":"Engineering, Technology & Applied Science Research","host_organization_lineage":["https://openalex.org/P4310318068"],"host_organization_lineage_names":["Engineering, Technology & Applied Science Research"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering, Technology & Applied Science Research","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.48084/etasr.20006","doi":"https://doi.org/10.48084/etasr.20006","is_oa":true,"landing_page_url":"https://doi.org/10.48084/etasr.20006","pdf_url":"https://www.etasr.com/index.php/ETASR/article/download/20006/7150","source":{"id":"https://openalex.org/S2737646863","display_name":"Engineering Technology & Applied Science Research","issn_l":"1792-8036","issn":["1792-8036","2241-4487"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310318068","host_organization_name":"Engineering, Technology & Applied Science Research","host_organization_lineage":["https://openalex.org/P4310318068"],"host_organization_lineage_names":["Engineering, Technology & Applied Science Research"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering, Technology & Applied Science Research","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7219106926.pdf","grobid_xml":"https://content.openalex.org/works/W7219106926.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2903907401","https://openalex.org/W2983040767","https://openalex.org/W3023528699","https://openalex.org/W3023911605","https://openalex.org/W3034309077","https://openalex.org/W3042667808","https://openalex.org/W3174770825","https://openalex.org/W3193668308","https://openalex.org/W4290648542","https://openalex.org/W4293078876","https://openalex.org/W4394565250","https://openalex.org/W4396753517","https://openalex.org/W4407066556","https://openalex.org/W4411120472","https://openalex.org/W4411766590","https://openalex.org/W4412740622","https://openalex.org/W4412889373","https://openalex.org/W4415883951","https://openalex.org/W7126415657","https://openalex.org/W7138165471"],"related_works":["https://openalex.org/W4378530943","https://openalex.org/W4417053667","https://openalex.org/W4415367794","https://openalex.org/W7139909392","https://openalex.org/W4292596092","https://openalex.org/W4416649855","https://openalex.org/W3082120522","https://openalex.org/W7197024626","https://openalex.org/W4385571293","https://openalex.org/W4414332769"],"abstract_inverted_index":{"Sentiment":[0,34],"analysis":[1,157],"in":[2,158],"low-resource":[3,159],"Indian":[4],"languages":[5],"such":[6],"as":[7],"Kannada":[8,119],"is":[9],"challenging":[10],"due":[11],"to":[12,49,74,91,97],"the":[13,19,31,61,83,127],"scarcity":[14,85],"of":[15,21,126,133],"annotated":[16],"data":[17,84,137],"and":[18,23,66,71,78,111,117,138,160],"presence":[20],"code-mixed":[22],"transliterated":[24],"text.":[25],"In":[26],"this":[27],"work,":[28],"we":[29],"propose":[30],"Language-Aware":[32],"Adaptive":[33],"Framework":[35],"(LAASF),":[36],"which":[37],"incorporates":[38],"an":[39,131],"adapter-based":[40],"fusion":[41,153],"strategy.":[42],"This":[43],"framework":[44,59],"performs":[45],"instance-level":[46],"model":[47,148],"selection":[48,149],"handle":[50],"diverse":[51],"input":[52],"types":[53],"within":[54],"a":[55,104],"single":[56],"system.":[57],"The":[58,143],"leverages":[60],"multilingual":[62,162],"transformer":[63],"models":[64],"MuRIL":[65],"XLM-RoBERTa":[67],"(XLM-R),":[68],"integrating":[69],"language-specific":[70],"sentiment-specific":[72],"adapters":[73],"effectively":[75],"combine":[76],"linguistic":[77],"sentiment":[79,93,156],"knowledge.":[80],"To":[81,99],"address":[82],"problem,":[86],"cross-lingual":[87],"alignment":[88],"was":[89,109],"performed":[90],"transfer":[92],"knowledge":[94],"from":[95],"English":[96],"Kannada.":[98],"improve":[100],"robustness":[101],"across":[102],"domains,":[103],"score-based":[105],"adaptive":[106,147],"ensemble":[107],"method":[108],"introduced":[110],"evaluated":[112],"on":[113,135,140],"native,":[114],"code-mixed,":[115],"transliterated,":[116],"mixed":[118,141],"datasets.":[120,142],"Experimental":[121],"results":[122],"demonstrated":[123],"strong":[124],"performance":[125],"proposed":[128],"model,":[129],"with":[130,151],"accuracy":[132],"0.80":[134],"native":[136],"0.77":[139],"findings":[144],"highlight":[145],"that":[146],"combined":[150],"adapter":[152],"enables":[154],"effective":[155],"heterogeneous":[161],"settings.":[163]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-04T00:00:00"}