The design and application of LLM-based personas in AI companionship is a rapidly expanding but fragmented field, spanning from virtual emotional companions and game NPCs to embodied functional robots. This diversity in objectives, modality, and technical stacks creates an urgent need for a unified framework. To address this gap, this paper systematizes the field by proposing a Four-Quadrant Technical Taxonomy for AI companion applications. The framework is structured along two critical axes: Virtual vs. Embodied and Emotional Companionship vs. Functional Augmentation. Quadrant I (Virtual Companionship) explores virtual idols, romantic companions, and story characters, introducing a four-layer technical framework to analyze their challenges in maintaining long-term emotional consistency. Quadrant II (Functional Virtual Assistants) analyzes AI applications in work, gaming, and mental health, highlighting the shift from "feeling" to "thinking and acting" and pinpointing key technologies like enterprise RAG and on-device inference. Quadrants III & IV (Embodied Intelligence) shift from the virtual to the physical world, analyzing home robots and vertical-domain assistants, revealing core challenges in symbol grounding, data privacy, and ethical liability. This taxonomy provides not only a systematic map for researchers and developers to navigate the complex persona design space but also a basis for policymakers to identify and address the unique risks inherent in different application scenarios.

翻译：基于LLM的角色在AI伴侣领域的设计与应用是一个快速扩张但高度碎片化的研究领域，涵盖从虚拟情感伴侣、游戏NPC到具身功能机器人的广泛场景。这种在目标、模态和技术栈上的多样性，亟需一个统一的框架来整合现有研究。为填补这一空白，本文通过提出面向AI伴侣应用的四象限技术分类法，对该领域进行了系统化梳理。该框架围绕两个关键维度构建：虚拟与具身、情感陪伴与功能增强。第一象限（虚拟陪伴）探讨虚拟偶像、浪漫伴侣和故事角色，引入四层技术框架分析其在维持长期情感一致性方面面临的挑战。第二象限（功能型虚拟助手）分析工作、游戏和心理健康领域的AI应用，强调从“感知”到“思考与行动”的范式转变，并指出企业RAG与端侧推理等关键技术。第三、四象限（具身智能）从虚拟世界转向物理世界，分析家庭机器人和垂直领域助手，揭示其在符号落地、数据隐私和伦理责任方面的核心挑战。该分类法不仅为研究者和开发者提供了系统化导航复杂角色设计空间的路线图，也为政策制定者识别和应对不同应用场景中特有的风险提供了依据。