variance-inference

This paper introduces Variational Linear Attention (VLA), a method that stabilizes memory states in linear attention mechanisms for long-context transformers. VLA reframes memory updates as an online regularized least-squares problem, proving bounded state norms and demonstrating significant speedups and improved retrieval accuracy over standard linear attention and DeltaNet.