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preliminary receiver positions. Despite these advances, current literature provides little guidance on how to systematically incorporate domain-specific constraints into the training and inference
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the student to guide the research, but preliminary ideas include: Exploring whether suggested discharge limits derived from single organism experiments are protective of microbial communities; Using Bayesian
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constrained and valid action space, enabling the generation of reliable answers in a single, efficient inference step. Third, an efficient Data-Driven Low-Rank Adaptation scheme will be employed to efficiently
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
will first exploit parameter-efficient fine-tuning techniques, e.g., pruning and quantisation, to reduce the complexity of LLMs. Then, distributed inference strategies and consensus mechanisms will be