Building Multi-Layered Safety Filters for LLMs to Combat Adaptive, Paraphrased, and Adversarial Prompt Attacks
In a significant move to enhance safety in AI systems, developers have created a multi-layered safety filter aimed at protecting large language models from various attacks. This innovative approach combines several techniques, including semantic similarity analysis, rule-based pattern detection, intent classification powered by a language model, and anomaly detection. The goal is to build a … Read more