SafePilot: A Framework for Assuring LLM-enabled Cyber-Physical Systems
Large Language Models (LLMs), deep learning architectures with typically over 10 billion parameters, have recently begun to be integrated into various cyber-physical systems (CPS) such as robotics, industrial automation, and autopilot systems. The abstract knowledge and reasoning capabilities of LLMs are employed for tasks like planning and navigation. However, a significant challenge arises from the tendency of LLMs to produce "hallucinations" - outputs that are coherent yet factually incorrect or contextually unsuitable. This characteristic can lead to undesirable or unsafe actions in the CPS. Therefore, our research focuses on assuring the LLM-enabled CPS by enhancing their critical pr...
| Authors | Weizhe Xu, Mengyu Liu, Fanxin Kong |
|---|---|
| Primary category | cs.RO |
| Published | 23 March 2026 |
| Last updated at source | 23 March 2026 |
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