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to search optimised model structures, complementing RL’s incremental updates. Consideration of robustness to various sources would be an objective too. Expected Contributions A novel framework combining
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to search optimised model structures, complementing RL’s incremental updates. Consideration of robustness to various sources would be an objective too. Expected Contributions A novel framework combining
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, GNSS positioning is highly susceptible to errors from atmospheric distortions, multipath effects, and receiver noise. Recent advances in deep learning have shown that data-driven pseudorange correction
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
-latency, and scalable operation in aerial 6G networks. In this regard, Large Language Models (LLMs) have recently emerged as a key technology to achieve adaptive 6G spectrum management. The core idea of LLM