agent/papers/items/2026-2605-14498-groupmembench-benchmarking-llm-agent-memory-in-multi-party-conversations.md

Paper: GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations

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type: paper title: "GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations" authors: Jingbo Yang, Kwei-Herng Lai, Xiaowen Wang, Shiyu Chang, Yaar Harari, Evgeniy Gabrilovich year: 2026 venue: arXiv url: https://arxiv.org/abs/2605.14498 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-05-14 updated_at: 2026-05-16 status: queued relevance: high topics:

• agent-evaluation
• computer-use
• memory
• rag
• reasoning methods:

benchmarks:

models:

datasets:

• cs.CL related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 21 collection_queries: agent-memory

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agent-memory
• inferred topics: agent-evaluation, computer-use, memory, rag, reasoning
• arXiv categories: cs.CL
• collection score: 21

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2605.14498