11 papers
Probabilistic Memory for Trustworthy Edge Intelligence
Likai Pei, Jiahao Zheng, Xueji Zhao +9
Probabilistic computation plays an important role in trustworthy edge intelligence to quantify uncertainty, enhance robustness, reconstruct data, and protect privacy, but its adopt…
When Small Variations Become Big Failures: Reliability Challenges in Compute-in-Memory Neural Accelerators
Yifan Qin, Jiahao Zheng, Zheyu Yan +3
Compute-in-memory (CiM) architectures promise significant improvements in energy efficiency and throughput for deep neural network acceleration by alleviating the von Neumann bottl…
Driving Through Uncertainty: Risk-Averse Control with LLM Commonsense for Autonomous Driving under Perception Deficits
Yuting Hu, Chenhui Xu, Ruiyang Qin +4
Partial perception deficits can compromise autonomous vehicle safety by disrupting environmental understanding. Existing protocols typically default to entirely risk-avoidant actio…
Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment Perspective
Zixuan Pan, Jun Xia, Zheyu Yan +7
Reconstruction-based methods, particularly those leveraging autoencoders, have been widely adopted for anomaly detection task in brain MRI. Unlike most existing works try to improv…
Tiny-Align: Bridging Automatic Speech Recognition and Large Language Model on the Edge
Ruiyang Qin, Dancheng Liu, Gelei Xu +7
The combination of Large Language Models (LLM) and Automatic Speech Recognition (ASR), when deployed on edge devices (called edge ASR-LLM), can serve as a powerful personalized ass…
PI-Whisper: Designing an Adaptive and Incremental Automatic Speech Recognition System for Edge Devices
Amir Nassereldine, Dancheng Liu, Chenhui Xu +3
Edge-based automatic speech recognition (ASR) technologies are increasingly prevalent in the development of intelligent and personalized assistants. However, resource-constrained A…