61 citations · 114 across the 6 of their papers we have counts for
6 papers
Improving Small Language Models on PubMedQA via Generative Data Augmentation
Zhen Guo, Peiqi Wang, Yanwei Wang +1
Large Language Models (LLMs) have made remarkable advancements in the field of natural language processing. However, their increasing size poses challenges in terms of computationa…
Sample-Specific Debiasing for Better Image-Text Models
Peiqi Wang, Yingcheng Liu, Ching-Yun Ko +4
Self-supervised representation learning on image-text data facilitates crucial medical applications, such as image classification, visual grounding, and cross-modal retrieval. One…
Using Multiple Instance Learning to Build Multimodal Representations
Peiqi Wang, William M. Wells, Seth Berkowitz +2
Image-text multimodal representation learning aligns data across modalities and enables important medical applications, e.g., image classification, visual grounding, and cross-moda…
FPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture
Yu Ji, Youyang Zhang, Xinfeng Xie +5
Neural Network (NN) accelerators with emerging ReRAM (resistive random access memory) technologies have been investigated as one of the promising solutions to address the \textit{m…
QGAN: Quantized Generative Adversarial Networks
Peiqi Wang, Dongsheng Wang, Yu Ji +5
The intensive computation and memory requirements of generative adversarial neural networks (GANs) hinder its real-world deployment on edge devices such as smartphones. Despite the…
Programmable Neural Network Trojan for Pre-Trained Feature Extractor
Yu Ji, Zixin Liu, Xing Hu +2
Neural network (NN) trojaning attack is an emerging and important attack model that can broadly damage the system deployed with NN models. Existing studies have explored the outsou…