2 citations · 2 across the 5 of their papers we have counts for
8 papers
When Is RTL Better? Auditing Evaluation Stability with Tool-Grounded Requirement Profiles
Bodong Hou, Zhixin Pan
RTL-generation studies increasingly report functional correctness and post-synthesis quality, yet the evaluator itself is rarely treated as an experimental variable. A candidate ca…
Hardware-Assisted Multi-Stage Ransomware Detection with Adaptive Machine Learning
Salma Aboelmagd, Md. Rakibul Ahasan, Zhixin Pan +2
Ransomware is a fast-escalating privacy threat causing significant financial and data losses worldwide. As attacks grow more sophisticated, traditional static signatures and dynami…
LatentIndex: Cross-Layer Sharing with Layer-Specific Selection for Sparse Attention
Zhaohui Wang, Zhixin Pan, Fanxu Meng +1
Sparse attention reduces core-attention computation, but its indexers still incur repeated selection work and per-layer key-cache storage. Reusing selected indices across layers re…
CARB: A Characterization-Guided Framework for CNN Inference Cost Prediction and Deployment Screening
Linh Nguyen, Zhixin Pan
Accurate pre-deployment estimation of CNN inference cost--energy, latency, and peak memory--is increasingly critical as models are deployed on resource-constrained GPU platforms. E…
HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention
Yufei Xu, Fanxu Meng, Fan Jiang +11
Token-level sparse attention mechanisms, exemplified by DeepSeek Sparse Attention (DSA), achieve fine-grained key selection by scoring every historical key for each query through a…
SAND: A Self-supervised and Adaptive NAS-Driven Framework for Hardware Trojan Detection
Zhixin Pan, Ziyu Shu, Linh Nguyen +1
The globalized semiconductor supply chain has made Hardware Trojans (HT) a significant security threat to embedded systems, necessitating the design of efficient and adaptable dete…
Towards Low-Latency and Adaptive Ransomware Detection Using Contrastive Learning
Zhixin Pan, Ziyu Shu, Amberbir Alemayoh
Ransomware has become a critical threat to cybersecurity due to its rapid evolution, the necessity for early detection, and growing diversity, posing significant challenges to trad…
SDIP: Self-Reinforcement Deep Image Prior Framework for Image Processing
Ziyu Shu, Zhixin Pan
Deep image prior (DIP) proposed in recent research has revealed the inherent trait of convolutional neural networks (CNN) for capturing substantial low-level image statistics prior…