arXiv: cs.AI preprintsInternational6 November 2026
ProMoral-Bench: Evaluating Prompting Strategies for Moral Reasoning and Safety in LLMs
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arXiv:2602.13274v2 Announce Type: replace Abstract: Prompt design affects the moral judgments and refusal behavior produced by large language models (LLMs), yet controlled comparisons remain fragmented across datasets and models. We introduce ProMoral-Bench, a benchmark-style comparison of 10 prompting paradigms across four LLM families. Using ETHICS, Scruples, WildJailbreak, and our 200-pair ETHICS-Contrast set, we report task-level metrics together with Moral Competence Score (MCS), jailbreak/over-refusal Safety Robustness Score (SRS), and Unified Moral Safety Score (UMSS). UMSS is a study-s
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