agent/papers/items/2026-2606-06399-collabsim-a-cscw-grounded-methodology-for-investigating-collaborative-competence.md

Paper: CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments

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type: paper title: "CollabSim: A CSCW-Grounded Methodology for Investigating Collaborative Competence of LLM Agents through Controlled Multi-Agent Experiments" authors: Jiaju Chen, Bo Sun, Yuxuan Lu, Yun Wang, Dakuo Wang, Bingsheng Yao year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.06399 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-04 updated_at: 2026-06-06 status: queued relevance: high topics:

• agent-evaluation
• agent-safety
• multi-agent
• planning
• reasoning
• tool-use
• world-model methods:

benchmarks:

models:

datasets:

• cs.CL related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 22 collection_queries: planning-agent

One-line Takeaway

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

Why Collected

• matched queries: planning-agent
• inferred topics: agent-evaluation, agent-safety, multi-agent, planning, reasoning, tool-use, world-model
• arXiv categories: cs.CL
• collection score: 22

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/2606.06399