dai-2023-momentum-based-attention-proposed
IN premise — summaries/2026/08/24/dai-2023-icl-gradient-descent-sR-references.md
Created 2026-08-24T17:10:54+00:00
Dai et al. 2023 propose a momentum-based attention mechanism inspired by the meta-optimization view, which yields consistent improvements over vanilla attention across the evaluated tasks.
Summary
Dai and colleagues (2023) showed that adding a momentum-like smoothing term to the attention mechanism in neural networks consistently outperforms standard attention on the tasks they evaluated. This matters because it suggests the core attention computation that every transformer relies on can be made more effective through a simple optimization-inspired tweak rather than a full architectural redesign.