5 citations · 10 across the 6 of their papers we have counts for
6 papers
DoGMA: A Central-Dogma-Guided Foundation Model for Multi-Omics Alignment and Multi-Task Learning in Oncology
Junfei Ling, Bangzheng Pu, Bingsen Xue +3
Attention mechanisms have been widely utilized in modern deep learning, and many existing multi-omics models inherit their conventional use to allow unrestricted bidirectional inte…
Cordon: Semantic Transactions for Tool-Using LLM Agents
Zheng Chen, Hanqing Liu, Duling Xu +4
Tool-using LLM agents are shifting the unit of computation from explicit human-issued commands to model-driven tasks with stateful consequences. Yet today's agent runtimes still ex…
SkillSmith: Compiling Agent Skills into Boundary-Guided Runtime Interfaces
Duling Xu, Zheng Chen, Zaifeng Pan +4
Recently, skills have been widely adopted in large language model (LLM)-based agent systems across various domains. In existing frameworks, skills are typically injected into the a…
SAM-Lightening: A Lightweight Segment Anything Model with Dilated Flash Attention to Achieve 30 times Acceleration
Yanfei Song, Bangzheng Pu, Peng Wang +4
Segment Anything Model (SAM) has garnered significant attention in segmentation tasks due to their zero-shot generalization ability. However, a broader application of SAMs to real-…
Preventing Unauthorized AI Over-Analysis by Medical Image Adversarial Watermarking
Xingxing Wei, Bangzheng Pu, Shiji Zhao +2
The advancement of deep learning has facilitated the integration of Artificial Intelligence (AI) into clinical practices, particularly in computer-aided diagnosis. Given the pivota…
Visual Adversarial Attacks and Defenses in the Physical World: A Survey
Xingxing Wei, Bangzheng Pu, Shiji Zhao +2
Although Deep Neural Networks (DNNs) have been widely applied in various real-world scenarios, they remain vulnerable to adversarial examples. Adversarial attacks in computer visio…