Unifying Attention and State Space Models: A New Framework

This ArXiv paper likely proposes a novel framework that bridges the gap between attention mechanisms and state space models, potentially leading to more efficient and powerful architectures. The unification could improve model performance across various sequence-based tasks.

• •Presents a unified framework.
• •Bridges attention and state space models.
• •Potential performance improvements in sequence tasks.