5 papers
LOGSAFE: Logic-Guided Verification for Trustworthy Federated Time-Series Learning
Dung Thuy Nguyen, Ziyan An, Taylor T. Johnson +2
This paper introduces LOGSAFE, a defense mechanism for federated learning in time series settings, particularly within cyber-physical systems. It addresses poisoning attacks by mov…
LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration
Zirong Chen, Ziyan An, Jennifer Reynolds +3
Emergency response services are critical to public safety, with 9-1-1 call-takers playing a key role in ensuring timely and effective emergency operations. To ensure call-taking pe…
Combining LLMs with Logic-Based Framework to Explain MCTS
Ziyan An, Xia Wang, Hendrik Baier +6
In response to the lack of trust in Artificial Intelligence (AI) for sequential planning, we design a Computational Tree Logic-guided large language model (LLM)-based natural langu…
Large Language Models for Traffic and Transportation Research: Methodologies, State of the Art, and Future Opportunities
Yimo Yan, Yejia Liao, Guanhao Xu +13
The rapid rise of Large Language Models (LLMs) is transforming traffic and transportation research, with significant advancements emerging between the years 2023 and 2025 -- a peri…
Enabling MCTS Explainability for Sequential Planning Through Computation Tree Logic
Ziyan An, Hendrik Baier, Abhishek Dubey +2
Monte Carlo tree search (MCTS) is one of the most capable online search algorithms for sequential planning tasks, with significant applications in areas such as resource allocation…