2 papers
cs.LG2026
Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation
Zunhai Su, Hengyuan Zhang, Wei Wu +24
As the foundational architecture of modern machine learning, Transformers have driven remarkable progress across diverse AI domains. Despite their transformative impact, a persiste…
cs.AR2024
SA-DS: A Dataset for Large Language Model-Driven AI Accelerator Design Generation
Deepak Vungarala, Mahmoud Nazzal, Mehrdad Morsali +4
In the ever-evolving landscape of Deep Neural Networks (DNN) hardware acceleration, unlocking the true potential of systolic array accelerators has long been hindered by the daunti…