{"id":"https://openalex.org/W7161246435","doi":"https://doi.org/10.48550/arxiv.2605.14498","title":"GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations","display_name":"GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations","publication_year":2026,"publication_date":"2026-05-14","ids":{"openalex":"https://openalex.org/W7161246435","doi":"https://doi.org/10.48550/arxiv.2605.14498"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.14498","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14498","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.14498","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136250764","display_name":"Jingbo Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Jingbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089183436","display_name":"Kwei-Herng Lai","orcid":"https://orcid.org/0000-0001-8933-7117"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Kwei-Herng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136194056","display_name":"Xiaowen Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xiaowen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136237454","display_name":"Shiyu Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang, Shiyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077735792","display_name":"Yaar Harari","orcid":"https://orcid.org/0000-0002-0549-8659"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harari, Yaar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5013932834","display_name":"Evgeniy Gabrilovich","orcid":"https://orcid.org/0000-0001-7933-1926"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gabrilovich, Evgeniy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.35659998655319214,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.35659998655319214,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.20239999890327454,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.13079999387264252,"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/benchmarking","display_name":"Benchmarking","score":0.6535999774932861},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5048999786376953},{"id":"https://openalex.org/keywords/memory-model","display_name":"Memory model","score":0.5012999773025513},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4772000014781952},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.4406000077724457},{"id":"https://openalex.org/keywords/semantic-memory","display_name":"Semantic memory","score":0.38029998540878296},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.33169999718666077},{"id":"https://openalex.org/keywords/memory-management","display_name":"Memory management","score":0.3264000117778778},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.32429999113082886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7911999821662903},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.6535999774932861},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5048999786376953},{"id":"https://openalex.org/C12186640","wikidata":"https://www.wikidata.org/wiki/Q6815743","display_name":"Memory model","level":3,"score":0.5012999773025513},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4772000014781952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46219998598098755},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.38029998540878296},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3528999984264374},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C176649486","wikidata":"https://www.wikidata.org/wiki/Q2308807","display_name":"Memory management","level":3,"score":0.3264000117778778},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C74426580","wikidata":"https://www.wikidata.org/wiki/Q719484","display_name":"Memory map","level":3,"score":0.3082999885082245},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3073999881744385},{"id":"https://openalex.org/C88576662","wikidata":"https://www.wikidata.org/wiki/Q18646","display_name":"Episodic memory","level":3,"score":0.304500013589859},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.2971999943256378},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.290800005197525},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C27853696","wikidata":"https://www.wikidata.org/wiki/Q3480151","display_name":"Interference theory","level":4,"score":0.2874000072479248},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2849000096321106},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2777000069618225},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C82687282","wikidata":"https://www.wikidata.org/wiki/Q66221","display_name":"Auxiliary memory","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C119907115","wikidata":"https://www.wikidata.org/wiki/Q6815725","display_name":"Memory errors","level":3,"score":0.2644999921321869},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25699999928474426},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.14498","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14498","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.14498","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.14498","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":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5864086151123047,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Model":[2],"(LLM)":[3],"agents":[4],"increasingly":[5],"serve":[6],"as":[7],"personal":[8],"assistants":[9],"and":[10,23,34,50,59,92,122,129,158,160,192,217],"workplace":[11],"collaborators,":[12],"where":[13,85,96],"their":[14],"utility":[15],"depends":[16,222],"on":[17,126],"memory":[18,32,70,88,169,173,207,212,221,226],"systems":[19,33,174],"that":[20,75,107,166],"extract,":[21],"retrieve,":[22],"apply":[24],"information":[25],"across":[26,144],"long-running":[27],"conversations.":[28],"However,":[29],"both":[30],"existing":[31],"benchmarks":[35],"are":[36],"built":[37],"around":[38],"the":[39,57,86,179,215],"dyadic,":[40],"single-user":[41],"setup,":[42],"even":[43],"though":[44],"real":[45],"deployments":[46],"routinely":[47],"span":[48],"groups":[49],"channels":[51],"with":[52,56,60,118,187],"multiple":[53],"users":[54],"interacting":[55],"agent":[58,206],"each":[61,124],"other.":[62],"This":[63,209],"mismatch":[64],"leaves":[65],"three":[66],"properties":[67],"of":[68],"group":[69,73,220],"unmeasured:":[71],"(i)":[72],"dynamics":[74],"go":[76],"beyond":[77],"concatenated":[78],"one-on-one":[79],"chats,":[80],"(ii)":[81],"speaker-grounded":[82],"belief":[83],"tracking,":[84],"per-user":[87,127],"modeling":[89],"is":[90],"needed,":[91],"(iii)":[93],"audience-adapted":[94],"language,":[95],"Theory-of-Mind":[97],"shifts":[98],"produce":[99],"role-specific":[100],"vocabulary.":[101],"We":[102],"introduce":[103],"GroupMemBench,":[104],"a":[105,141,176,198],"benchmark":[106],"exposes":[108,175],"all":[109],"three.":[110],"A":[111],"graph-grounded":[112],"synthesis":[113],"pipeline":[114,135],"produces":[115],"multi-party":[116],"conversations":[117],"controllable":[119],"reply":[120],"structure":[121],"conditions":[123],"message":[125],"personas":[128],"target":[130],"audiences.":[131],"An":[132],"adversarial":[133],"query":[134],"then":[136],"binds":[137],"every":[138],"question":[139],"to":[140],"specific":[142],"asker":[143],"six":[145],"categories,":[146],"spanning":[147],"multi-hop":[148],"reasoning,":[149,155,157],"knowledge":[150,188],"update,":[151],"term":[152,193],"ambiguity,":[153],"user-implicit":[154],"temporal":[156],"abstention,":[159],"iteratively":[161],"searches":[162],"challenging,":[163],"realistic":[164],"queries":[165],"reflect":[167],"comprehensive":[168],"capability.":[170],"Benchmarking":[171],"leading":[172],"sharp":[177],"collapse:":[178],"strongest":[180],"one":[181],"reaches":[182],"only":[183],"46.0%":[184],"average":[185],"accuracy,":[186],"update":[189],"at":[190,195],"27.1%":[191],"ambiguity":[194],"37.7%,":[196],"while":[197],"simple":[199],"BM25":[200],"baseline":[201],"matches":[202],"or":[203],"exceeds":[204],"most":[205],"systems.":[208],"indicates":[210],"current":[211],"ingestion":[213],"erases":[214],"structural":[216],"lexical":[218],"features":[219],"on,":[223],"leaving":[224],"multi-user":[225],"far":[227],"from":[228],"solved.":[229]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-16T00:00:00"}
