@inproceedings{dong-etal-2026-pear,
    title = "{PEAR}: Planner-Executor Agent Robustness Benchmark",
    author = "Dong, Shen  and
      Zhang, Mingxuan  and
      He, Pengfei  and
      Ma, Li  and
      Thuraisingham, Bhavani  and
      Liu, Hui  and
      Xing, Yue",
    editor = "Demberg, Vera  and
      Inui, Kentaro  and
      Marquez, Llu{\'i}s",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EACL} 2026",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.findings-eacl.237/",
    pages = "4547--4567",
    ISBN = "979-8-89176-386-9",
    abstract = "Large Language Model (LLM){--}based Multi-Agent Systems (MAS) have emerged as a powerful paradigm for tackling complex, multi-step tasks across diverse domains. However, despite their impressive capabilities, MAS remain susceptible to adversarial manipulation. Existing studies typically examine isolated attack surfaces or specific scenarios, leaving a lack of holistic understanding of MAS vulnerabilities. To bridge this gap, we introduce PEAR, a benchmark for systematically evaluating both the utility and vulnerability of planner{--}executor MAS. While compatible with various MAS architectures, our benchmark focuses on the planner{--}executor structure{---}a practical and widely adopted design. Through extensive experiments, we find that (1) a weak planner degrades overall clean task performance more severely than a weak executor; (2) while a memory module is essential for the planner, incorporating a memory module into the executor yields only marginal improvements in clean-task performance; (3) there exists a trade-off between task performance and robustness; and (4) attacks targeting the planner are particularly effective at misleading the system. These findings offer actionable insights for enhancing the robustness of MAS and lay the groundwork for principled defenses in multi-agent settings."
}