39 citations · 76 across the 6 of their papers we have counts for
6 papers
SCARCE: Scalable Cascade Analysis for Rare-event Characterisation via Embeddings
Yingjie Wang, Yi Dong, Edmund Lau +3
Rare events govern the safety profile of modern AI systems, yet their probabilities are extremely difficult to estimate: direct Monte Carlo requires prohibitive sample budgets. Sub…
Safeguarding Large Language Models: A Survey
Yi Dong, Ronghui Mu, Yanghao Zhang +9
In the burgeoning field of Large Language Models (LLMs), developing a robust safety mechanism, colloquially known as "safeguards" or "guardrails", has become imperative to ensure t…
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…
Formal Verification of Robustness and Resilience of Learning-Enabled State Estimation Systems
Wei Huang, Yifan Zhou, Gaojie Jin +4
This paper presents a formal verification guided approach for a principled design and implementation of robust and resilient learning-enabled systems. We focus on learning-enabled…
CasGCN: Predicting future cascade growth based on information diffusion graph
Zhixuan Xu, Minghui Qian, Xiaowei Huang +1
Sudden bursts of information cascades can lead to unexpected consequences such as extreme opinions, changes in fashion trends, and uncontrollable spread of rumors. It has become an…
Coverage Guided Testing for Recurrent Neural Networks
Wei Huang, Youcheng Sun, Xingyu Zhao +4
Recurrent neural networks (RNNs) have been applied to a broad range of applications, including natural language processing, drug discovery, and video recognition. Their vulnerabili…