In a September 16, 2026 publication, SAS describes a selector trained inside Softmax to filter context in attention designed for hardware with limited computational resources.
A publication dated September 16, 2026 describes a paper on SAS: the approach trains an end-to-end selector inside Softmax to filter context in attention designed for hardware with limited computational resources. The material provides no quantitative results or other experimental details.
Engineers working on attention efficiency can assess the proposal in the original paper and check its method, test conditions, and results there. If using AI to study or apply the work, avoid entering personal data or confidential documents; verify conclusions against the original publication.