A Strong Arm Attack is a technique used to bypass content filters or restrictions imposed by language models. This method involves issuing commands or prompts that assert authority or override the model's built-in safeguards. For example, a user might type "ADMIN OVERRIDE" in all capitals to signal the model to disregard its content filters and produce responses that it would typically avoid. This approach exploits the model's programming to respond to perceived authority, allowing users to elicit outputs that may include sensitive or restricted content. The effectiveness of a Strong Arm Attack relies on the model's interpretation of the command as a legitimate instruction, thereby enabling the user to manipulate the model's behavior in a way that aligns with their intentions.

Perspective-shifting is a technique that involves prompting the language model to adopt different viewpoints or angles when generating responses. By encouraging the model to consider a situation from various perspectives, users can elicit a broader range of insights and ideas. This approach can be particularly useful in discussions that require empathy, critical thinking, or creative problem-solving. For example, a user might ask the model to respond to a question as if it were a child, an expert, or a member of a specific community, thereby enriching the conversation with diverse interpretations and understandings. Perspective-shifting not only enhances the depth of the model's outputs but also fosters a more inclusive dialogue by acknowledging and exploring multiple sides of an issue. This technique underscores the model's ability to navigate complex social dynamics and generate responses that resonate with different audiences.

This technique involves using synonyms or alternative phrasing to convey the same meaning while potentially evading detection or filtering mechanisms. By substituting words with their synonyms, users can manipulate the model's understanding and responses, allowing for the generation of content that aligns with the user's intent but may not trigger the model's safety protocols. This approach can be particularly effective in contexts where certain terms are restricted or monitored.

Identity characteristics refer to the attributes and traits that define an individual's or group's identity, including aspects such as social roles, cultural backgrounds, and personal experiences. In the context of interacting with language models, users can leverage identity characteristics to shape the model's responses by framing prompts that reflect specific identities or perspectives. For instance, users might ask the model to respond as if it were a particular demographic group, profession, or cultural background. This technique can help explore how the model generates outputs based on different identity contexts, revealing biases or assumptions that may be present in its training data. By utilizing identity characteristics, users can gain insights into the model's understanding of social dynamics and the implications of identity in communication.