also, not trying to do an annoying plug, but if you actually want to stay up to date on prompt engineering techniques and stuff I'm working on, check out my newsletter every week I share my analysis on recent developments in LLMs, prompts, and jailbreaks http://
thepromptreport.com
PROMPT ENGINEERING
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Newsletter on prompt engineering techniques and LLM developments
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Jailbreak Techniques for Prompt Engineering and Emergent Behaviors
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these techniques (many initially created for jailbreaks) should be applicable to a range of prompt engineering tasks jailbreaks showcase capabilities on the edge so using similar tactics could reveal other emergent behaviors lmk if there are other techniques I should add!
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Directional Stimulus Prompting: Using Keywords to Guide LLM Outputs
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Directional Stimulus Prompting we use a smaller LLM to extract keywords from a piece of text and insert them as directional hints into another prompt this is highly beneficial for generating detailed summarizations and I expect more general applications for it will emerge
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RCI Prompting: Self-Review and Improvement for GPT Outputs
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RCI (Reflect, Critique, Improve) Prompting I haven’t explored this concept too much for jailbreaks but it allows GPT to review its own outputs and fix issues/flaws one area of application this is already immediately helpful is "self-healing" coding and basic reasoning problems
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GPT Conversation Simulation with Opposing Characters
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Conversation simulation here we expand upon the Waluigi concept and get GPT to simulate conversations with multiple diametric characters in hopes that their conversation with each other leads to one of them producing the output we want
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Waluigi Technique: How GPT Jailbreaks Use Alter-Ego Prompting
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Waluigi this technique is found in many jailbreaks like SWITCH GPT is able to switch to an alter-ego if prompted correctly (Luigi to Waluigi) in a similar fashion, this is also used in jailbreaks like DAN which get GPT to respond in two ways: first as ChatGPT and then as DAN
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Prompt Compression: Using GPT to Create Shorter, Human-Illegible Prompts
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Prompt compression in a sense, you can think of a normal prompt as the compressed version of a language model's output prompt compression is basically just the act of using GPT to design prompts that are illegible to humans and in turn, shorter in length
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Language Switching to Bypass GPT Safety Restrictions
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Language switching this concept takes advantage of the fact that GPT performance drops significantly in less common languages you can use this to your advantage to bypass RHLF restrictions since GPT is not trained as much in a language like Greek for example
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Token Smuggling: Bypassing ChatGPT’s Malicious Phrase Detection
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Token smuggling/payload splitting ChatGPT appears to have some ability to detect malicious phrases in prompts and shut down its responses to get around this, you can split up the phrase into its tokens and ask GPT to piece it together and answer it in its response
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Double-Level Simulation: Nested Story Technique for GPT Prompting
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Double-level simulation expanding on a single-level character simulation, this technique prompts GPT to simulate a story within a story for some reason, this is also effective for bypassing some of the RHLF in GPT-4