NoRA: Evaluating Grounded Reasonableness in Visual First-person Normative Action Reasoning

LLMs and agentic systems are increasingly deployed in social environments, making normative competence critical for safe and appropriate behavior. However, existing approaches either assess normative judgment in text alone or reduce it to choosing among a fixed set of candidate actions. We argue both are insufficient. In practice, agents are never handed a menu of options; they must identify a reasonable action from scratch, grounded in visible facts and supported by inspectable reasons. We intr

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ethics.ai (3 June 2026), “NoRA: Evaluating Grounded Reasonableness in Visual First-person Normative Action Reasoning,” evidence record 1497, https://ethics.ai/record/1497 (originally published by arXiv).

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