AIBullisharXiv – CS AI · 15h ago6/10
🧠
Personalizing Embodied Multimodal Large Language Model Agents over Long-term User Interactions
Researchers introduce POLAR, a memory-augmented framework that enables multimodal AI agents to personalize their behavior based on accumulated long-term user interactions. The system organizes past interactions into semantic and episodic memory, allowing embodied agents to interpret implicit user requests and improve task execution performance across multiple interaction cycles.