arXiv:2605.02335v1 Announce Type: cross
Abstract: Large Language Models (LLMs) have transformed agent-agent and human-agent interaction by enabling software, physical, and simulation agents to communicate and deliberate through natural language. Yet fluent language use does not by itself yield socially intelligible behaviour. Most current systems remain weakly grounded in roles, norms, intentions, and contextual constraints, limiting their capacity for meaningful participation in social environments. This paper develops a conceptual baseline for LLM-enabled social agents by arguing that they should be grounded in role definitions operationalized through persona descriptions. On this basis, we outline research directions for representation, hybrid control, and evaluation. The paper concludes that persona-based role definitions are a necessary foundation for turning language competence into social behaviour.
Development of a high-performance in-memory database architecture for intelligent video surveillance in critical patient care
ObjectivesThis research aims to engineer a specialized, high-speed database architecture tailored for intelligent video surveillance in critical healthcare environments. The primary objective is to overcome