Optimizing Latency and Energy Efficiency in Edge-Native Large Language Models (LLMs) for Autonomous Mobile Agents
This study introduces an edge-native framework for optimizing latency and energy efficiency in LLM-enabled autonomous mobile agents and shows decreased communication overhead, increased operational continuity, and faster response times without significantly lowering language comprehension or decision-making precision.