RoleCDE:Benchmarking and Mitigating Role-Alignment Trade-offs in Role-Playing Agents

Role-playing agents(RPAs) are widely used to steer large language models(LLMs) toward role-consistent behavior, yet existing benchmarks mainly evaluate surface-level fidelity and offer limited insight into decision making under role-alignment value conflicts. To address this gap, we introduce RoleCDE, the first benchmark designed to evaluate RPAs under structured conflicts between role-specific values and alignment-oriented constraints. RoleCDE formulates role-aware decision making as cognitive

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ethics.ai (1 June 2026), “RoleCDE:Benchmarking and Mitigating Role-Alignment Trade-offs in Role-Playing Agents,” evidence record 3317, https://ethics.ai/record/3317 (originally published by arXiv).

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