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arXiv · 2610.25208

BrandEval: A Two-Track Multi-Agent Benchmark for Risk-Sensitive LLM Crisis Communication

Haotian Gan·Weidong Tang·Hanbin Sun·Yi Luo·Xintian Li·Jiayong Wang·WanYue Li·Yudong Li
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Abstract

Evaluating LLMs for crisis communication requires more than judging isolated responses, because public feedback and competitor actions can reshape trust over time. Existing benchmarks remain largely static and single-turn, offering limited evidence about long-horizon risk-sensitive communication. We introduce \textbf{BrandEval}, a two-track benchmark for product-crisis communication, focusing on public brand responses to product-related safety, quality, service, and trust incidents. BrandEval-Static evaluates stakeholder-aware strategic analysis, while BrandEval-Dynamic stress-tests response policies in \textbf{BrandPolis}, a controlled multi-agent sandbox with consumer feedback, competitor responses, and trust-risk trajectories. We also construct \textbf{BrandSRD}, a Chinese crisis-response dataset, and instantiate a reference Strategic Agent using \textbf{Strategic Rationale (SR)}. Across proprietary and open-source models, we find that static strategic quality is informative but incomplete: it aligns with some end-state outcomes but does not reliably predict volatility and delayed recovery; dynamic stress tests further expose tail-risk failures under manipulative or weakly grounded policies. The code and dataset will be available at https://github.com/htgan-ai/BrandEval.

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Haotian Gan, Weidong Tang, Hanbin Sun, Yi Luo, Xintian Li, Jiayong Wang, WanYue Li, Yudong Li. 2026-10-18. BrandEval: A Two-Track Multi-Agent Benchmark for Risk-Sensitive LLM Crisis Communication. https://arxiv.org/abs/2610.25208

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