agent/papers/items/2026-2606-08340-benchmarking-open-ended-multi-agent-coordination-in-language-agents.md

Paper: Benchmarking Open-Ended Multi-Agent Coordination in Language Agents

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type: paper title: Benchmarking Open-Ended Multi-Agent Coordination in Language Agents authors: Kale-ab Abebe Tessera, Andras Szecsenyi, Cameron Barker, Alexander Rutherford, Davide Paglieri, Aidan Scannell, Henry Gouk, Elliot J. Crowley, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.08340 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-06 updated_at: 2026-06-06 status: queued relevance: high topics:

• agent-evaluation
• memory
• multi-agent
• planning
• rag
• reasoning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.AI
• cs.LG
• cs.MA related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 28 collection_queries: autonomous-agent-llm, language-agent, planning-agent

One-line Takeaway

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

Why Collected

• matched queries: autonomous-agent-llm, language-agent, planning-agent
• inferred topics: agent-evaluation, memory, multi-agent, planning, rag, reasoning, tool-use
• arXiv categories: cs.AI, cs.LG, cs.MA
• collection score: 28

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/2606.08340