agent/papers/items/2026-2606-22082-codeteam-an-llm-powered-multi-agent-framework-for-repository-level-code-generati.md

Paper: CodeTeam: An LLM-Powered Multi-Agent Framework for Repository-Level Code Generation

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type: paper title: "CodeTeam: An LLM-Powered Multi-Agent Framework for Repository-Level Code Generation" authors: Yifei Wang, Ruiyin Li, Peng Liang, Qiong Feng, Zengyang Li, Mojtaba Shahin, Arif Ali Khan year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.22082 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-20 updated_at: 2026-06-20 status: queued relevance: high topics:

• agent-evaluation
• coding-agent
• multi-agent
• planning
• rag methods:

benchmarks:

models:

datasets:

• cs.SE
• cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: multi-agent-llm

One-line Takeaway

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

Why Collected

• matched queries: multi-agent-llm
• inferred topics: agent-evaluation, coding-agent, multi-agent, planning, rag
• arXiv categories: cs.SE, cs.AI
• collection score: 16

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/2606.22082