{"id":"https://openalex.org/W4412888415","doi":"https://doi.org/10.18653/v1/2025.findings-acl.601","title":"Optima: Optimizing Effectiveness and Efficiency for LLM-Based Multi-Agent System","display_name":"Optima: Optimizing Effectiveness and Efficiency for LLM-Based Multi-Agent System","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412888415","doi":"https://doi.org/10.18653/v1/2025.findings-acl.601"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2025.findings-acl.601","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.601","pdf_url":"https://aclanthology.org/2025.findings-acl.601.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":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.findings-acl.601.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006645143","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0002-8018-4529"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weize Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119181413","display_name":"Jiarui Yuan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiarui Yuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067505422","display_name":"Qian Chen","orcid":"https://orcid.org/0000-0003-1691-5777"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen Qian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Cheng Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320723","display_name":"Zhiyuan Liu","orcid":"https://orcid.org/0000-0002-7709-2543"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiyuan Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Maosong Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maosong Sun","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":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"11534","last_page":"11557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.8615000247955322,"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/T10456","display_name":"Multi-Agent Systems and Negotiation","score":0.8615000247955322,"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/computer-science","display_name":"Computer science","score":0.6480799317359924},{"id":"https://openalex.org/keywords/multi-agent-system","display_name":"Multi-agent system","score":0.4601472318172455},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23629000782966614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6480799317359924},{"id":"https://openalex.org/C41550386","wikidata":"https://www.wikidata.org/wiki/Q529909","display_name":"Multi-agent system","level":2,"score":0.4601472318172455},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23629000782966614}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.findings-acl.601","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.601","pdf_url":"https://aclanthology.org/2025.findings-acl.601.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":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.findings-acl.601","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.findings-acl.601","pdf_url":"https://aclanthology.org/2025.findings-acl.601.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":"Findings of the Association for Computational Linguistics: ACL 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320329860","display_name":"National Science and Technology Major Project","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412888415.pdf","grobid_xml":"https://content.openalex.org/works/W4412888415.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Model":[2],"(LLM)":[3],"based":[4,140],"multiagent":[5],"systems":[6],"(MAS)":[7],"show":[8],"remarkable":[9],"potential":[10,190],"in":[11,51,184],"collaborative":[12],"problem-solving,":[13],"yet":[14],"they":[15],"still":[16],"face":[17],"critical":[18],"challenges:":[19],"low":[20],"communication":[21,46,75],"efficiency,":[22,73],"poor":[23],"scalability,":[24],"and":[25,48,62,74,86,125,131,137,194],"a":[26,35,66],"lack":[27],"of":[28],"effective":[29,170,195],"parameter-updating":[30],"optimization":[31],"methods.We":[32],"present":[33],"OPTIMA,":[34],"novel":[36],"framework":[37],"that":[38],"addresses":[39],"these":[40],"issues":[41],"by":[42],"significantly":[43],"enhancing":[44],"both":[45],"efficiency":[47,166],"task":[49,70],"effectiveness":[50],"LLM-based":[52,185],"MAS":[53,139],"through":[54],"training.OPTIMA":[55],"employs":[56],"an":[57],"iterative":[58],"generate,":[59],"rank,":[60],"select,":[61],"train":[63],"paradigm":[64],"with":[65,154],"reward":[67],"function":[68],"balancing":[69],"performance,":[71],"token":[72],"readability.We":[76],"explore":[77,113],"various":[78],"algorithms,":[79],"including":[80,121],"Supervised":[81],"Fine-Tuning,":[82],"Direct":[83],"Preference":[84],"Optimization,":[85],"their":[87,93],"hybrid":[88],"approaches,":[89],"providing":[90],"insights":[91],"into":[92],"effectiveness-efficiency":[94],"trade-offs.We":[95],"integrate":[96],"Monte":[97],"Carlo":[98],"Tree":[99],"Search-inspired":[100],"techniques":[101],"for":[102],"DPO":[103],"data":[104],"generation,":[105],"treating":[106],"conversation":[107],"turns":[108],"as":[109],"tree":[110],"nodes":[111],"to":[112,150,176],"diverse":[114],"interaction":[115],"paths.Evaluated":[116],"on":[117,141,159],"common":[118],"multi-agent":[119],"tasks,":[120],"information-asymmetric":[122],"question":[123],"answering":[124],"complex":[126],"reasoning,":[127],"OPTIMA":[128,187],"shows":[129,188],"consistent":[130],"substantial":[132],"improvements":[133],"over":[134],"single-agent":[135],"baselines":[136],"vanilla":[138],"Llama":[142],"3":[143],"8B":[144],"/":[145],"3.2":[146],"3B,":[147],"achieving":[148],"up":[149],"2.8x":[151],"performance":[152],"gain":[153],"less":[155],"than":[156],"10%":[157],"tokens":[158],"tasks":[160],"requiring":[161],"heavy":[162],"information":[163],"exchange.Moreover,":[164],"OPTIMA's":[165],"gains":[167],"enable":[168],"more":[169],"compute":[171],"utilization":[172],"during":[173],"inference,":[174],"leading":[175],"improved":[177],"inferencetime":[178],"scaling":[179],"laws.By":[180],"addressing":[181],"fundamental":[182],"challenges":[183],"MAS,":[186],"the":[189],"towards":[191],"scalable,":[192],"efficient,":[193],"MAS.Our":[196],"code":[197],"is":[198],"available":[199],"at":[200],"https://github.com/thunlp/Optima.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}