most citedToward Foundation Models for Online Complex Event Detection in CPS-IoT: A Case Study

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CR2025

Preliminary Investigation into Uncertainty-Aware Attack Stage Classification

Alessandro Gaudenzi, Lorenzo Nodari, Lance Kaplan +3

Advanced Persistent Threats (APTs) represent a significant challenge in cybersecurity due to their prolonged, multi-stage nature and the sophistication of their operators. Traditio…

cs.LG20251 cited

Toward Foundation Models for Online Complex Event Detection in CPS-IoT: A Case Study

Liying Han, Gaofeng Dong, Xiaomin Ouyang +3

Complex events (CEs) play a crucial role in CPS-IoT applications, enabling high-level decision-making in domains such as smart monitoring and autonomous systems. However, most exis…

cs.LG2025

ADMN: A Layer-Wise Adaptive Multimodal Network for Dynamic Input Noise and Compute Resources

Jason Wu, Yuyang Yuan, Kang Yang +2

Multimodal deep learning systems are deployed in dynamic scenarios due to the robustness afforded by multiple sensing modalities. Nevertheless, they struggle with varying compute r…

cs.LG2025

NAROCE: A Neural Algorithmic Reasoner Framework for Online Complex Event Detection

Liying Han, Gaofeng Dong, Xiaomin Ouyang +3

Modern machine learning models excel at detecting individual actions, objects, or scene attributes from short, local observations. However, many real-world tasks, such as in smart…

cs.LG2024

Risk-aware Classification via Uncertainty Quantification

Murat Sensoy, Lance M. Kaplan, Simon Julier +2

Autonomous and semi-autonomous systems are using deep learning models to improve decision-making. However, deep classifiers can be overly confident in their incorrect predictions,…