Social Norm Reasoning in Multimodal Language Models: An Evaluation
In Multi-Agent Systems (MAS), agents are designed with social capabilities, allowing them to understand and reason about social concepts such as norms when interacting with others (e.g., inter-robot interactions). In Normative MAS (NorMAS), researchers study how norms develop, and how violations are detected and sanctioned. However, existing research in NorMAS use symbolic approaches (e.g., formal logic) for norm representation and reasoning whose application is limited to simplified environments. In contrast, Multimodal Large Language Models (MLLMs) present promising possibilities to develop software used by robots to identify and reason about norms in a wide variety of complex social si...
| Authors | Oishik Chowdhury, Anushka Debnath, Bastin Tony Roy Savarimuthu |
|---|---|
| Primary category | cs.MA |
| Published | 3 March 2026 |
| Last updated at source | 3 March 2026 |
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