{"id":"https://openalex.org/W4416035444","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.1594","title":"LoRACoE: Improving Large Language Model via Composition-based LoRA Expert","display_name":"LoRACoE: Improving Large Language Model via Composition-based LoRA Expert","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416035444","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.1594"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.emnlp-main.1594","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1594","pdf_url":"https://aclanthology.org/2025.emnlp-main.1594.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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.emnlp-main.1594.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012696718","display_name":"Guanyu Li","orcid":"https://orcid.org/0000-0001-9639-5825"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Guanyu Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036875405","display_name":"Zhiheng Xi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiheng Xi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361527","display_name":"Zhihao Zhang","orcid":"https://orcid.org/0000-0001-8213-5790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhihao Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109730221","display_name":"Boyang Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Boyang Hong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058353652","display_name":"Tao Gui","orcid":"https://orcid.org/0000-0002-6154-0751"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao Gui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114180092","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-9336-0755"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5088834359","display_name":"Xuanjing Huang","orcid":"https://orcid.org/0000-0001-9197-9426"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuanjing Huang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5012696718"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1717813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"31278","last_page":"31292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.30550000071525574,"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/T10028","display_name":"Topic Modeling","score":0.30550000071525574,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.09719999879598618,"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":0.04639999940991402,"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/language-model","display_name":"Language model","score":0.3693999946117401},{"id":"https://openalex.org/keywords/expert-system","display_name":"Expert system","score":0.31119999289512634},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.30809998512268066},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.288100004196167},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.27720001339912415},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.2770000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6492000222206116},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3693999946117401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3671000003814697},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.30809998512268066},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2969000041484833},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.288100004196167},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C179603123","wikidata":"https://www.wikidata.org/wiki/Q1941921","display_name":"Modeling language","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2517000138759613},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.emnlp-main.1594","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1594","pdf_url":"https://aclanthology.org/2025.emnlp-main.1594.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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.emnlp-main.1594","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.1594","pdf_url":"https://aclanthology.org/2025.emnlp-main.1594.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 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327803","display_name":"Shanghai Rising-Star Program","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416035444.pdf","grobid_xml":"https://content.openalex.org/works/W4416035444.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Mixture":[1],"of":[2,69,105,113,159],"Experts":[3],"(MoE)":[4],"architecture":[5],"improves":[6],"large":[7],"language":[8],"models":[9],"(LLMs)":[10],"by":[11,47],"utilizing":[12],"sparsely":[13],"activated":[14],"expert":[15],"sub-networks":[16],"with":[17,118],"a":[18,38,119,156],"routing":[19],"module,":[20],"yet":[21],"it":[22,121],"typically":[23],"demands":[24],"high":[25],"training":[26],"cost.Previous":[27],"work":[28],"introduces":[29],"parameter-efficient":[30],"fine-tuning":[31],"(PEFT)":[32],"modules,":[33,85],"e.g.,":[34],"LoRA,":[35],"to":[36,144],"achieve":[37],"lightweight":[39],"MoE":[40,147],"for":[41],"efficiency.However,":[42],"they":[43],"construct":[44],"static":[45],"experts":[46,106,124,131],"manually":[48],"splitting":[49],"the":[50,66,74,80,96,103,109],"LoRA":[51,71,84,138],"parameters":[52,91,136],"into":[53,79],"fixed":[54],"groups,":[55],"which":[56],"limits":[57],"flexibility":[58],"and":[59,107],"dynamism.Furthermore,":[60],"this":[61],"manual":[62],"partitioning":[63],"also":[64],"hinders":[65],"effective":[67],"utilization":[68],"well-initialized":[70],"modules.To":[72],"tackl":[73],"challenges,":[75],"we":[76,101],"first":[77],"delve":[78],"parameter":[81,128],"patterns":[82],"in":[83,137],"revealing":[86],"that":[87,92,142],"there":[88],"exists":[89],"task-relevant":[90],"are":[93],"concentrated":[94],"along":[95],"rank":[97],"dimension.Based":[98],"on":[99,126],"this,":[100],"redesign":[102],"construction":[104],"propose":[108],"LoRACoE":[110],"(LoRA":[111],"Composition":[112],"Experts)":[114],"method.Specifically,":[115],"when":[116],"confronted":[117],"task,":[120],"dynamically":[122],"builds":[123],"based":[125],"rank-level":[127,135],"composition,":[129],"i.e.,":[130],"can":[132],"flexibly":[133],"combine":[134],"module.Extensive":[139],"experiments":[140],"demonstrate":[141],"compared":[143],"other":[145],"LoRA-based":[146],"methods,":[148],"our":[149],"method":[150],"achieves":[151],"better":[152],"task":[153],"performance":[154],"across":[155],"broader":[157],"range":[158],"tasks.":[160]},"counts_by_year":[],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-11-08T00:00:00"}
