This project investigates the limitations of traditional Large Language Models and introduces Large Concept Models (LCMs) as an emerging paradigm for advanced AI reasoning. It highlights abstraction challenges and demonstrates how concept-level representations improve semantic reasoning and contextual understanding across domains.
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ChatNVD explores the application of Large Language Models to improve vulnerability assessment and interpretation by integrating the National Vulnerability Database and delivering context-rich cybersecurity insights.
View ProjectSmart HPA introduces a resource-efficient auto-scaling framework for microservice architectures operating in constrained environments, enabling coordinated scaling and improved system resilience.
This project proposes a microservice-based MAPE-K architecture to overcome the limitations of monolithic self-adaptive cybersecurity frameworks while supporting scalable and autonomous security management.