4 papers · 1 filter
GenQ: Quantization in Low Data Regimes with Generative Synthetic Data
Yuhang Li, Youngeun Kim, Donghyun Lee +2
In the realm of deep neural network deployment, low-bit quantization presents a promising avenue for enhancing computational efficiency. However, it often hinges on the availabilit…
ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition
Shiting Xiao, Yuhang Li, Youngeun Kim +2
Spiking Neural Networks (SNNs) have emerged as a compelling, energy-efficient alternative to traditional Artificial Neural Networks (ANNs) for static image tasks such as image clas…
Do We Really Need a Large Number of Visual Prompts?
Youngeun Kim, Yuhang Li, Abhishek Moitra +2
Due to increasing interest in adapting models on resource-constrained edges, parameter-efficient transfer learning has been widely explored. Among various methods, Visual Prompt Tu…
One-stage Prompt-based Continual Learning
Youngeun Kim, Yuhang Li, Priyadarshini Panda
Prompt-based Continual Learning (PCL) has gained considerable attention as a promising continual learning solution as it achieves state-of-the-art performance while preventing priv…