The Cross-modal SleepTransformer is a deep learning model designed for sleep stage classification based on multimodal physiological signals. It utilizes the transformer architecture, and cross-attention mechanism to effectively process and integrate information from multiple input modalities, including EEG, EOG, EMG, ECG, and respiratory signals.