Twilight: Adaptive Attention Sparsity with Hierarchical Top-$p$ Pruning
NeutralArtificial Intelligence
A recent paper discusses the challenges of using attention sparsity in large language models, particularly focusing on the limitations of current algorithms that rely on fixed budgets. This research is significant as it highlights the need for more adaptable solutions that can better balance accuracy and efficiency in real-world applications, which is crucial for the deployment of these advanced models.
— Curated by the World Pulse Now AI Editorial System



