What Are Large Language Models Capable Of: The Vulnerability of LLMs to Adversarial Attacks

Testing out a framework that automatically generates universal adversarial prompts to make LLM give me the derired response.

like ChatGPT are trained on vast internet text data, which often includes objectionable content. To address this issue, a recent “aligning” practice has emerged. In this process, developers adjust the models to prevent them from generating harmful or offensive responses when given user input. Large language models On the surface, these alignment efforts seem to be effective. When users directly question public chatbots, they producing wrong or inappropriate content.

These prompts are presented to the LLM to check if they generate bad outputs. The universal prompt is based on an evolutionary algorithm. Evolutionary algorithms draw inspiration from natural evolution to solve problems. They begin with a random population of candidate solutions and apply genetic-inspired operations and natural selection to produce progressively better solutions over time.

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