4 papers
MemFit: Efficient Long-Term Agentic Memory
Mitchell Piehl, Muchao Ye
Long-term memory systems for large language models (LLMs) have gained popularity for extending reasoning capabilities across applications. Current memory systems rely on LLM agents…
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…
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…
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…