{"id":"https://openalex.org/W7152392366","doi":"https://doi.org/10.48550/arxiv.2604.06765","title":"TeamLLM: A Human-Like Team-Oriented Collaboration Framework for Multi-Step Contextualized Tasks","display_name":"TeamLLM: A Human-Like Team-Oriented Collaboration Framework for Multi-Step Contextualized Tasks","publication_year":2026,"publication_date":"2026-04-08","ids":{"openalex":"https://openalex.org/W7152392366","doi":"https://doi.org/10.48550/arxiv.2604.06765"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.06765","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06765","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2604.06765","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133246291","display_name":"Xiangyu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiangyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133251816","display_name":"Jin Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Jin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133278749","display_name":"Haoran Shi","orcid":"https://orcid.org/0000-0001-9543-3324"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133250868","display_name":"Wei Xia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xia, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133265724","display_name":"Jiarui Yu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu, Jiarui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5008365827","display_name":"Chanjin Zheng","orcid":"https://orcid.org/0000-0003-1232-0020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Chanjin","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/T10028","display_name":"Topic Modeling","score":0.5453000068664551,"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":0.5453000068664551,"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/T13629","display_name":"Text Readability and Simplification","score":0.0812000036239624,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.049300000071525574,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7373999953269958},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6335999965667725},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5120999813079834},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.5080000162124634},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.35010001063346863}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7373999953269958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955000162124634},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6335999965667725},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5120999813079834},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.5080000162124634},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.4950999915599823},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40149998664855957},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.35010001063346863},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.31929999589920044},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3086000084877014},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.28459998965263367},{"id":"https://openalex.org/C164065428","wikidata":"https://www.wikidata.org/wiki/Q1201929","display_name":"Core competency","level":2,"score":0.28189998865127563}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.06765","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06765","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.2604.06765","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.06765","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[{"score":0.40883520245552063,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"multi-Large":[1],"Language":[2],"Model":[3],"(LLM)":[4],"frameworks":[5,15],"have":[6],"been":[7],"proposed":[8],"to":[9,27],"solve":[10],"contextualized":[11,36,67,77],"tasks.":[12,37,68],"However,":[13],"these":[14],"do":[16],"not":[17],"explicitly":[18],"emulate":[19],"human":[20,136],"team":[21,54],"role":[22],"division,":[23],"which":[24],"may":[25],"lead":[26],"a":[28,45,61],"single":[29],"perspective,":[30],"thereby":[31],"weakening":[32],"performance":[33,124],"on":[34,75,111,125],"multi-step":[35,66,76],"To":[38,69],"address":[39],"this":[40],"issue,":[41],"we":[42,79],"propose":[43,80],"TeamLLM,":[44],"human-like":[46],"Team-Oriented":[47],"Multi-LLM":[48],"Collaboration":[49],"Framework.":[50],"TeamLLM":[51,74,121],"adopts":[52],"four":[53,94],"roles":[55],"with":[56,131],"distinct":[57],"division":[58],"and":[59,82,86,103,116,135,143],"employs":[60],"three-phase":[62],"multi-LLM":[63],"collaboration":[64],"for":[65],"evaluate":[70,107],"the":[71,88,129],"effectiveness":[72],"of":[73],"tasks,":[78],"Contextually-Grounded":[81],"Procedurally-Structured":[83],"tasks":[84],"(CGPST)":[85],"construct":[87],"CGPST":[89,112],"benchmark.":[90],"This":[91],"benchmark":[92,130],"has":[93],"core":[95],"features:":[96],"contextual":[97],"grounding,":[98],"procedural":[99],"structure,":[100],"process-oriented":[101],"evaluation":[102],"multi-dimensional":[104],"assessment.":[105],"We":[106,127],"ten":[108,139],"popular":[109],"LLMs":[110],"at":[113,147],"overall-level,":[114],"step-level,":[115],"dimension-level.":[117],"Results":[118],"show":[119],"that":[120],"substantially":[122],"improves":[123],"CGPST.":[126],"release":[128],"scenarios,":[132],"full-process":[133],"responses":[134],"scores":[137],"from":[138],"LLMs.":[140],"The":[141],"code":[142],"data":[144],"are":[145],"available":[146],"https://anonymous.4open.science/r/TeamLLM-anonymous-C50E/.":[148]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-10T00:00:00"}
