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The paper proposes CRAFT, a data-centric method for fine-tuning small language models to enable pre-hoc explainability in AI-native 6G RAN, achieving higher accuracy and energy efficiency compared to existing methods like GRPO.
This survey provides a comprehensive review of wireless foundation models, covering architectures, pre-training paradigms, applications, and challenges for AI-native 6G networks.