Planning Capability

Research on planning capability in large language models (LLMs) focuses on enhancing their ability to generate and execute sequences of actions to achieve goals, addressing limitations in their current planning performance. Current efforts involve developing novel architectures like Large Reasoning Models (LRMs) and incorporating techniques such as history-aware planning, multimodal information fusion, and retrieval-augmented planning to improve plan generation and robustness. These advancements are significant because improved planning capabilities in LLMs could lead to more sophisticated AI agents for diverse applications, from robotics and gaming to complex decision-making systems.