28 citations · 113 across the 10 of their papers we have counts for
10 papers
Privacy-Preserving Distributed Learning for Residential Short-Term Load Forecasting
Yi Dong, Yingjie Wang, Mariana Gama +3
In the realm of power systems, the increasing involvement of residential users in load forecasting applications has heightened concerns about data privacy. Specifically, the load d…
Building Guardrails for Large Language Models
Yi Dong, Ronghui Mu, Gaojie Jin +6
As Large Language Models (LLMs) become more integrated into our daily lives, it is crucial to identify and mitigate their risks, especially when the risks can have profound impacts…
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation
Xiaowei Huang, Wenjie Ruan, Wei Huang +14
Large Language Models (LLMs) have exploded a new heatwave of AI for their ability to engage end-users in human-level conversations with detailed and articulate answers across many…
STPA for Learning-Enabled Systems: A Survey and A New Practice
Yi Qi, Yi Dong, Siddartha Khastgir +3
Systems Theoretic Process Analysis (STPA) is a systematic approach for hazard analysis that has been used across many industrial sectors including transportation, energy, and defen…
Reachability Verification Based Reliability Assessment for Deep Reinforcement Learning Controlled Robotics and Autonomous Systems
Yi Dong, Xingyu Zhao, Sen Wang +1
Deep Reinforcement Learning (DRL) has achieved impressive performance in robotics and autonomous systems (RAS). A key challenge to its deployment in real-life operations is the pre…
Short-term Load Forecasting with Distributed Long Short-Term Memory
Yi Dong, Yang Chen, Xingyu Zhao +1
With the employment of smart meters, massive data on consumer behaviour can be collected by retailers. From the collected data, the retailers may obtain the household profile infor…
Reliability Assessment and Safety Arguments for Machine Learning Components in System Assurance
Yi Dong, Wei Huang, Vibhav Bharti +6
The increasing use of Machine Learning (ML) components embedded in autonomous systems -- so-called Learning-Enabled Systems (LESs) -- has resulted in the pressing need to assure th…
Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems through Probabilistic Model Checking
Yi Dong, Xingyu Zhao, Xiaowei Huang
While Deep Reinforcement Learning (DRL) provides transformational capabilities to the control of Robotics and Autonomous Systems (RAS), the black-box nature of DRL and uncertain de…
Detecting Operational Adversarial Examples for Reliable Deep Learning
Xingyu Zhao, Wei Huang, Sven Schewe +2
The utilisation of Deep Learning (DL) raises new challenges regarding its dependability in critical applications. Sound verification and validation methods are needed to assure the…
There is Limited Correlation between Coverage and Robustness for Deep Neural Networks
Yizhen Dong, Peixin Zhang, Jingyi Wang +7
Deep neural networks (DNN) are increasingly applied in safety-critical systems, e.g., for face recognition, autonomous car control and malware detection. It is also shown that DNNs…