arXiv cs.CL· Rishabh Mediratta, Lingyun Xiao, Peter Stone, Joydeep Biswas, Elias Stengel-Eskin·· 11 小时前AI 评分52
ParallACT：共享代码库中多智能体协调与通信基准
Decentralized Multi-Agent Coordination and Communication in Shared Codebases
AI 导读
研究团队提出 ParallACT，一个无编排器的多智能体编码基准，包含互补任务与矛盾任务两类。实验显示并行智能体明显弱于单智能体 oracle，矛盾任务上 Claude Code 搭配 Claude Opus 4.8 从 62% 降至 16%，且告知智能体存在同伴帮助不大，开放通信通道只挽回小部分性能并增加 token 开销。
正文 · 原文
Abstract:Coding agents working in shared repositories may receive separate, independently-motivated requests from human developers, creating a setting that is multi-agent by necessity. When this scenario happens, their individual implementations may work separately but conflict when combined. To study this setting, we introduce ParallACT, a benchmark of orchestrator-free multi-agent coding tasks. ParallACT contains both complementary and contradictory tasks. In complementary tasks, each agent's task is separately useful and implementations must share an interface to be productively combined. In contradictory pairs, both agents' tasks require editing the same code in incompatible ways, and naively combining independent solutions fails to produce a useful implementation. We compare a single-agent oracle given the combined set of tasks against multi-agent settings that vary execution order, visibility, awareness of other agents, and access to a communication channel. We find that the oracle solves most tasks while parallel agents perform substantially worse. Their performance drop is notable for complementary tasks, and particularly sharp for contradictory tasks (e.g., from 62% to 16% for Claude Code with Claude Opus 4.8) where merged code typically satisfies only one specification, and the same gap appears in all six further configurations pairing two agent harnesses with three open-weight models. Simply telling an agent that a peer exists does not help significantly, and giving agents access to a communication channel recovers only a small part of the performance, at an additional token cost. ParallACT thus identifies and isolates a core challenge that will become more common as multi-agent coding by independent principals becomes standard, and provides a controlled test of which coordination strategies help, and at what cost.
| Comments: | First two authors contributed equally. Project Page: this https URL |
| Subjects: | Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Multiagent Systems (cs.MA) |
| Cite as: | arXiv:2611.00314 [cs.AI] |
| (or arXiv:2611.00314v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2611.00314 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Rishabh Mediratta [view email]
[v1]
Fri, 30 Oct 2026 19:36:54 UTC (334 KB)
来源：arXiv cs.CL · arxiv.org