On Integrating Resilience and Human Oversight into LLM-Assisted Modeling Workflows for Digital Twins

1. 1Identify potential hallucination risks in LLM-assisted modeling workflows
2. 2Design human oversight mechanisms to detect and correct errors
3. 3Implement real-time model adaptability to ensure resilience in changing environments

Data scientists, AI engineers, and product managers on a team benefit from this research as it provides guidance on designing robust LLM-assisted modeling workflows for Digital Twins, enabling them to build more reliable and adaptable models

💡 Integrating resilience and human oversight into LLM-assisted modeling workflows is essential for building reliable and adaptable Digital Twins

💡 Ensure reliable Digital Twins with LLM-assisted modeling by integrating resilience and human oversight