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Instruction-level feedback from audio-aware LLMs can drastically enhance the accuracy of multi-event audio generation, bridging a critical gap in current models.
Achieving state-of-the-art ECG analysis performance with a lightweight framework that minimizes resource usage could revolutionize self-supervised learning in healthcare.
RobOralScan achieves a remarkable 92.58% average coverage in robotic intraoral scanning, significantly enhancing automation in dental procedures.
