9 citations · 9 across the 6 of their papers we have counts for
6 papers
Transfer Learning for Minimum Operating Voltage Prediction in Advanced Technology Nodes: Leveraging Legacy Data and Silicon Odometer Sensing
Yuxuan Yin, Rebecca Chen, Boxun Xu +2
Accurate prediction of chip performance is critical for ensuring energy efficiency and reliability in semiconductor manufacturing. However, developing minimum operating voltage ($V…
Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning
Boxun Xu, Yuxuan Yin, Vikram Iyer +1
We present Bishop, the first dedicated hardware accelerator architecture and HW/SW co-design framework for spiking transformers that optimally represents, manages, and processes sp…
Towards 3D Acceleration for low-power Mixture-of-Experts and Multi-Head Attention Spiking Transformers
Boxun Xu, Junyoung Hwang, Pruek Vanna-iampikul +3
Spiking Neural Networks(SNNs) provide a brain-inspired and event-driven mechanism that is believed to be critical to unlock energy-efficient deep learning. The mixture-of-experts a…
Towards the Mitigation of Confirmation Bias in Semi-supervised Learning: a Debiased Training Perspective
Yu Wang, Yuxuan Yin, Peng Li
Semi-supervised learning (SSL) commonly exhibits confirmation bias, where models disproportionately favor certain classes, leading to errors in predicted pseudo labels that accumul…
DS2TA: Denoising Spiking Transformer with Attenuated Spatiotemporal Attention
Boxun Xu, Hejia Geng, Yuxuan Yin +1
Vision Transformers (ViT) are current high-performance models of choice for various vision applications. Recent developments have given rise to biologically inspired spiking transf…
S3: Side-Channel Attack on Stylus Pencil through Sensors
Habiba Farrukh, Tinghan Yang, Hanwen Xu +3
With smart devices being an essential part of our everyday lives, unsupervised access to the mobile sensors' data can result in a multitude of side-channel attacks. In this paper,…