8 citations · 11 across the 10 of their papers we have counts for
10 papers
Schema-Agnostic Knowledge Graph Construction via Hybrid Ontology Discovery for Cyber Threat Intelligence
Seonwoo Kim, Jinwoo Kim, Daegyu Kang +2
Cyber threat intelligence (CTI) reports now serve as essential resources for capturing adversary tactics, techniques, and procedures observed in modern attack campaigns. While trad…
SafeVLA-Bench: A Benchmark for the Success-Safety Gap in Vision-Language-Action Models
Jialiang Fan, Weizhe Xu, Oleg Sokolsky +3
Vision-language-action (VLA) benchmarks measure whether a policy completes a requested manipulation task, but binary success can hide safety violations along the trajectory: a poli…
SafeGen-LLM: Enhancing Safety Generalization in Task Planning for Robotic Systems
Jialiang Fan, Weizhe Xu, Mengyu Liu +3
Safety-critical task planning in robotic systems remains challenging: classical planners suffer from poor scalability, Reinforcement Learning (RL)-based methods generalize poorly,…
Conservative Perception Models for Probabilistic Verification
Matthew Cleaveland, Pengyuan Lu, Oleg Sokolsky +2
Verifying the behaviors of autonomous systems with learned perception components is a challenging problem due to the complexity of the perception and the uncertainty of operating e…
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties
Xiayan Ji, Anton Xue, Eric Wong +2
Anomaly detection is widely used for identifying critical errors and suspicious behaviors, but current methods lack interpretability. We leverage common properties of existing meth…
Automating Weak Label Generation for Data Programming with Clinicians in the Loop
Jean Park, Sydney Pugh, Kaustubh Sridhar +7
Large Deep Neural Networks (DNNs) are often data hungry and need high-quality labeled data in copious amounts for learning to converge. This is a challenge in the field of medicine…
Recovery from Adversarial Attacks in Cyber-physical Systems: Shallow, Deep and Exploratory Works
Pengyuan Lu, Lin Zhang, Mengyu Liu +4
Cyber-physical systems (CPS) have experienced rapid growth in recent decades. However, like any other computer-based systems, malicious attacks evolve mutually, driving CPS to unde…
Testing learning-enabled cyber-physical systems with Large-Language Models: A Formal Approach
Xi Zheng, Aloysius K. Mok, Ruzica Piskac +5
The integration of machine learning (ML) into cyber-physical systems (CPS) offers significant benefits, including enhanced efficiency, predictive capabilities, real-time responsive…
Repairing Learning-Enabled Controllers While Preserving What Works
Pengyuan Lu, Matthew Cleaveland, Oleg Sokolsky +2
Learning-enabled controllers have been adopted in various cyber-physical systems (CPS). When a learning-enabled controller fails to accomplish its task from a set of initial states…
IBCL: Zero-shot Model Generation under Stability-Plasticity Trade-offs
Pengyuan Lu, Michele Caprio, Eric Eaton +1
Algorithms that balance the stability-plasticity trade-off are well studied in the Continual Learning literature. However, only a few focus on obtaining models for specified trade-…