{"id":"https://openalex.org/W7138943849","doi":"https://doi.org/10.48550/arxiv.2603.17094","title":"Evaluating LLM-Simulated Conversations in Modeling Inconsistent and Uncollaborative Behaviors in Human Social Interaction","display_name":"Evaluating LLM-Simulated Conversations in Modeling Inconsistent and Uncollaborative Behaviors in Human Social Interaction","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7138943849","doi":"https://doi.org/10.48550/arxiv.2603.17094"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.17094","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17094","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2603.17094","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129998922","display_name":"Ryo Kamoi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kamoi, Ryo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066652607","display_name":"Ameya Godbole","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Godbole, Ameya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130163713","display_name":"Longqi Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Longqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129928169","display_name":"Rui Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Rui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046172814","display_name":"Mengting Wan","orcid":"https://orcid.org/0000-0002-5298-1221"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wan, Mengting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129873492","display_name":"Pei Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Pei","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":0.4043999910354614,"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":0.4043999910354614,"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":0.0706000030040741,"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"}},{"id":"https://openalex.org/T12128","display_name":"AI in Service Interactions","score":0.04410000145435333,"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/set","display_name":"Set (abstract data type)","score":0.6543999910354614},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.515999972820282},{"id":"https://openalex.org/keywords/human-behavior","display_name":"Human behavior","score":0.48159998655319214},{"id":"https://openalex.org/keywords/proxy","display_name":"Proxy (statistics)","score":0.4756999909877777},{"id":"https://openalex.org/keywords/social-relation","display_name":"Social relation","score":0.45350000262260437},{"id":"https://openalex.org/keywords/dyad","display_name":"Dyad","score":0.3970000147819519}],"concepts":[{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6543999910354614},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.515999972820282},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.49140000343322754},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48399999737739563},{"id":"https://openalex.org/C117035363","wikidata":"https://www.wikidata.org/wiki/Q3769299","display_name":"Human behavior","level":2,"score":0.48159998655319214},{"id":"https://openalex.org/C2780148112","wikidata":"https://www.wikidata.org/wiki/Q1432581","display_name":"Proxy (statistics)","level":2,"score":0.4756999909877777},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.4575999975204468},{"id":"https://openalex.org/C130064352","wikidata":"https://www.wikidata.org/wiki/Q853725","display_name":"Social relation","level":2,"score":0.45350000262260437},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.4309999942779541},{"id":"https://openalex.org/C2777716012","wikidata":"https://www.wikidata.org/wiki/Q5318389","display_name":"Dyad","level":2,"score":0.3970000147819519},{"id":"https://openalex.org/C2987082051","wikidata":"https://www.wikidata.org/wiki/Q223642","display_name":"Human interaction","level":2,"score":0.3880999982357025},{"id":"https://openalex.org/C2993724205","wikidata":"https://www.wikidata.org/wiki/Q315","display_name":"Human language","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.29089999198913574},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C131158328","wikidata":"https://www.wikidata.org/wiki/Q1307337","display_name":"Social influence","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C2780829048","wikidata":"https://www.wikidata.org/wiki/Q1624720","display_name":"Conversation analysis","level":3,"score":0.2578999996185303},{"id":"https://openalex.org/C2776352735","wikidata":"https://www.wikidata.org/wiki/Q2313343","display_name":"Turn-taking","level":3,"score":0.2565000057220459},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.17094","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17094","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.17094","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.17094","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.6008975505828857,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Simulating":[0],"human":[1,16,21,118,148,179,201,214],"conversations":[2,22,48,76,111,119,139,180],"using":[3,90],"large":[4],"language":[5],"models":[6],"(LLMs)":[7],"has":[8],"emerged":[9],"as":[10,34,126,128,161,192,210],"a":[11,186,211],"scalable":[12],"methodology":[13],"for":[14,213],"modeling":[15],"social":[17,62,215],"interaction.":[18,63,216],"However,":[19],"simulating":[20,58,200],"is":[23,55],"challenging":[24],"because":[25],"they":[26],"inherently":[27],"involve":[28],"inconsistent":[29,40,82,143],"and":[30,36,41,46,60,83,99,116,123,144,174],"uncollaborative":[31,42,84,145],"behaviors,":[32,160,190],"such":[33,191],"misunderstandings":[35],"interruptions.":[37],"Analysis":[38],"comparing":[39,104],"behaviors":[43,54,85,109,146],"in":[44,110,117],"human-":[45],"LLM-generated":[47],"remains":[49],"limited,":[50],"although":[51],"reproducing":[52],"these":[53,159],"integral":[56],"to":[57,169,184],"human-like":[59],"complex":[61],"In":[64],"this":[65],"work,":[66],"we":[67,95],"introduce":[68],"CoCoEval,":[69,94],"an":[70,91],"evaluation":[71],"framework":[72],"that":[73,133,165],"analyzes":[74],"LLM-simulated":[75,138],"by":[77,103,113],"detecting":[78],"10":[79],"types":[80],"of":[81,107,189,199,208],"at":[86],"the":[87,105,197,206],"turn":[88],"level":[89],"LLM-as-a-Judge.":[92],"Using":[93],"evaluate":[96],"GPT-4.1,":[97],"GPT-5.1,":[98],"Claude":[100],"Opus":[101],"4":[102],"frequencies":[106],"detected":[108],"simulated":[112],"each":[114],"model":[115],"across":[120],"academic,":[121],"business,":[122],"governmental":[124],"meetings,":[125],"well":[127],"debates.":[129],"Our":[130,194],"analysis":[131],"shows":[132],"(1)":[134],"under":[135],"vanilla":[136],"prompting,":[137],"exhibit":[140],"far":[141],"fewer":[142],"than":[147],"conversations;":[149],"(2)":[150],"prompt":[151],"engineering":[152],"does":[153],"not":[154],"provide":[155],"reliable":[156],"control":[157],"over":[158],"our":[162],"results":[163],"show":[164],"different":[166],"prompts":[167],"lead":[168,182],"their":[170],"under-":[171],"or":[172],"overproduction;":[173],"(3)":[175],"supervised":[176],"fine-tuning":[177],"on":[178],"can":[181],"LLMs":[183,209],"overproduce":[185],"narrow":[187],"set":[188],"repetition.":[193],"findings":[195],"highlight":[196],"difficulty":[198],"conversations,":[202],"raising":[203],"concerns":[204],"about":[205],"use":[207],"proxy":[212]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-20T00:00:00"}