Security Related

Research in security is rapidly evolving to address vulnerabilities arising from the increasing use of AI and machine learning in various applications, from autonomous vehicles to medical devices and large language models. Current efforts focus on developing robust defenses against adversarial attacks, data poisoning, and privacy breaches, often employing techniques like differential privacy, federated learning, and advanced cryptographic methods alongside novel model architectures such as retrieval-augmented generation and mixture-of-experts models. This work is crucial for ensuring the trustworthiness and reliability of AI systems and protecting sensitive data in a wide range of critical sectors.