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Reason Popper-ly: Patching In-Context Reasoning with Inductive Logic Programming
Zirong Chen, Meiyi Ma
Chain-of-thought (CoT) prompting enables large language models (LLMs) to tackle multi-step reasoning tasks, yet the generated intermediate steps are not guaranteed to be logically…
Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly Detection
Yilin Liu, Hongchao Zhang, Taylor T. Johnson +2
Graph anomaly detection methods aim to distinguish anomalous nodes. While prior methods characterize anomalies through increased variation in the spectral energy distributions, the…
Identifying Adversary Characteristics from an Observed Attack
Soyon Choi, Scott Alfeld, Meiyi Ma
When used in automated decision-making systems, machine learning (ML) models are vulnerable to data-manipulation attacks. Some defense mechanisms (e.g., adversarial regularization)…
PACE: A Personalized Adaptive Curriculum Engine for 9-1-1 Call-taker Training
Zirong Chen, Hongchao Zhang, Meiyi Ma
9-1-1 call-taking training requires mastery of over a thousand interdependent skills, covering diverse incident types and protocol-specific nuances. A nationwide labor shortage is…
BEAGLE: Behavior-Enforced Agent for Grounded Learner Emulation
Hanchen David Wang, Clayton Cohn, Zifan Xu +3
Simulating student learning behaviors in open-ended problem-solving environments holds potential for education research, from training adaptive tutoring systems to stress-testing p…
Empowering 9-1-1 Calltaking Training with Generative AI: Experiences and Lessons Learned
Zirong Chen, Meiyi Ma
Emergency call-takers form the first operational link in public safety response, handling over 240 million calls annually while facing a sustained training crisis: staffing shortag…