Part 7/10:
Despite its promise, Hydra Attention is not without caveats:
It currently works best with dense images and homogeneous token regimes.
As image resolutions grow, the benefits become more pronounced, but validation on tasks with more tokens and sparser data remains ongoing.
The authors acknowledge that local window attention—another technique used in Vision Transformers—may still be more effective in certain scenarios, especially where sparse tokens or masked training are involved.
Further research will explore mixing Hydra with other attention strategies and extending its applicability beyond vision.