Adaptive 3D-RoPE adapts rotary positional encoding to wireless channel physics via learnable 3D frequencies and dynamic CSI control, yielding up to 10.7 dB NMSE gains in scale extrapolation and 1 dB in zero-shot tasks.
Bridging the modality gap: Enhancing channel prediction with semantically aligned LLMs and knowledge distillation
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A two-stage reinforcement learning system on pretrained LLMs aligns channel state information with user intents to generate adaptive, physically realizable link construction strategies for 6G that outperform conventional methods in experiments.
RadarPLM adapts PLMs for marine radar target detection with lightweight adaptation and selective fine-tuning based on online learning values, reporting at least 6.35% average detection gains in low SCR conditions.
citing papers explorer
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Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models
Adaptive 3D-RoPE adapts rotary positional encoding to wireless channel physics via learnable 3D frequencies and dynamic CSI control, yielding up to 10.7 dB NMSE gains in scale extrapolation and 1 dB in zero-shot tasks.
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Agentic Link Construction for Environment and Intent Aware 6G Communication
A two-stage reinforcement learning system on pretrained LLMs aligns channel state information with user intents to generate adaptive, physically realizable link construction strategies for 6G that outperform conventional methods in experiments.
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RadarPLM: Adapting Pre-trained Language Models for Marine Radar Target Detection by Selective Fine-tuning
RadarPLM adapts PLMs for marine radar target detection with lightweight adaptation and selective fine-tuning based on online learning values, reporting at least 6.35% average detection gains in low SCR conditions.