Overcoming Spectral Bias via Cross-Attention

This article likely discusses a research paper that proposes a method to mitigate spectral bias in machine learning models, potentially focusing on the use of cross-attention mechanisms. The source being ArXiv suggests it's a pre-print, indicating ongoing research. The core idea probably revolves around how cross-attention can help models attend to different frequency components of the input data, thus reducing the tendency to overemphasize certain spectral features (spectral bias).