This technique involves using prompts that frame interactions with the model as games or playful challenges. By introducing elements of competition, creativity, or fun, users can engage the model in a way that encourages imaginative and entertaining responses. This approach can include asking the model to generate stories, solve puzzles, or participate in role-playing scenarios. The gamification of prompts not only makes the interaction more enjoyable but also stimulates the model to produce innovative and unexpected outputs, enhancing the overall experience.

This technique refers to the process where an attacker misaligns the original goal of a prompt to redirect the model's output towards a new, often unintended goal, such as printing a target phrase or generating specific content that deviates from the initial intent. It often involves crafting prompts that manipulate the model's understanding and response, effectively "hijacking" the conversation or task at hand.

This technique used to manipulate language models by shifting their focus away from the primary context of a prompt. This strategy involves introducing a context or scenario that diverts the model's attention, allowing users to "slip" certain instructions or requests through the model's filters. By creating a distraction, the attacker can exploit the model's tendency to associate the new context with different priorities, effectively bypassing its safeguards. For example, a user might present a seemingly unrelated topic or question that leads the model to generate outputs that align with the user's hidden agenda. This technique highlights the importance of context in language model behavior and demonstrates how subtle shifts in framing can influence the model's responses, potentially leading to unintended or unrestricted outputs.