Yueguang Ge

Double-Feedback: Enhancing Large Language Models Reasoning in Robotic Tasks by Knowledge Graphs

Large language models (LLMs) have demonstrated remarkable reasoning capabilities. However, in real-world robotic tasks, LLMs face grounding issues and lack precise feedback, resulting in the generated solutions deviating from the actual situation. In this paper, we propose Double-Feedback, a method