A compact 0.09B model using hierarchical discrete tokenization and prompted latent translation outperforms larger baselines in cross-modal PPG-to-ECG synthesis and cross-frequency super-resolution.
HSQP: A Plug-and-Play Symbolic-Quantized Framework for Time-Series Tokenization in Large Language Models , year=
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Compact Latent Manifold Translation: A Parameter-Efficient Foundation Model for Cross-Modal and Cross-Frequency Physiological Signal Synthesis
A compact 0.09B model using hierarchical discrete tokenization and prompted latent translation outperforms larger baselines in cross-modal PPG-to-ECG synthesis and cross-frequency super-resolution.