PReD: An LLM-based Foundation Multimodal Model for Electromagnetic Perception, Recognition, and Decision

1. 1Construct a foundation model for the electromagnetic domain using LLMs
2. 2Integrate domain knowledge to address data scarcity and improve model performance
3. 3Apply the model to perception, recognition, and decision-making tasks in the EM domain
4. 4Evaluate and fine-tune the model for optimal results

Researchers and engineers in the electromagnetic domain can benefit from PReD, as it provides a foundation for intelligent closed-loop processing, while AI engineers and ML researchers can leverage PReD's architecture for similar applications

💡 PReD addresses the challenges of data scarcity and insufficient domain knowledge integration in the electromagnetic domain using LLMs

💡 PReD: An LLM-based foundation model for electromagnetic perception, recognition, and decision-making