3 papers
cs.CV2026
LATERN: Test-Time Context-Aware Explainable Video Anomaly Detection
Mitchell Piehl, Muchao Ye
Vision-language models (VLMs) have recently emerged as a promising paradigm for video anomaly detection (VAD) due to their strong visual reasoning ability and natural language-base…
cs.LG2026
ER-MIA: Black-Box Adversarial Memory Injection Attacks on Long-Term Memory-Augmented Large Language Models
Mitchell Piehl, Zhaohan Xi, Zuobin Xiong +2
Large language models (LLMs) are increasingly augmented with long-term memory systems to overcome finite context windows and enable persistent reasoning across interactions. Howeve…
cs.AI2025
Solving Math Word Problems Using Estimation Verification and Equation Generation
Mitchell Piehl, Dillon Wilson, Ananya Kalita +1
Large Language Models (LLMs) excel at various tasks, including problem-solving and question-answering. However, LLMs often find Math Word Problems (MWPs) challenging because solvin…