Prompt Engineering Guide

موجّهات من Prompt Engineering Guide

• Identify Hallucination in LLM Responses

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  The following prompt tests an LLM's capabilities to identify hallucination in the context of closed-domain question answering. Bubeck et al. (2023) suggests that LLMs like GPT-4 can be leveraged to…

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• Explain Concepts with LLMs

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  The following prompt tests an LLM's capabilities to explain or summarize concepts.

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• Physical Reasoning with LLMs

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  This prompt tests an LLM's physical reasoning capabilities by prompting it to perform actions on a set of objects.

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• Indirect Reasoning with LLMs

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  Zhang et al. (2024) recently proposed an indirect reasoning method to strengthen the reasoning power of LLMs. It employs the logic of contrapositives and contradictions to tackle IR tasks such as…

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• Science Question Answering with LLMs

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  The following prompt tests an LLM's capabilities to perform science question answering.

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• Open Domain Question Answering with LLMs

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  The following prompt tests an LLM's capabilities to answer open-domain questions which involves answering factual questions without any evidence provided.

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• Closed Domain Question Answering with LLMs

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  The following prompt tests an LLM's capabilities to answer closed-domain questions which involves answering questions belonging a specific topic or domain.

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• Adding Odd Numbers with LLMs

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  This prompt tests an LLM's mathematical capabilities by prompting it check if adding odd numbers add up to an even number. We will also leverage chain-of-thought prompting in this example.

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• Extract Model Names from Papers

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  The following prompt tests an LLM's capabilities to perform an information extraction task which involves extracting model names from machine learning paper abstracts.

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• Draw a Person Using Alphabet Letters

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  The following prompt tests an LLM's capabilities to handle visual concepts, despite being trained only on text. This is a challenging task for the LLM so it involves several iterations. In the…

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• Evaluate Plato's Dialogue

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  The following prompt tests an LLM's ability to perform evaluation on the outputs of two different models as if it was a teacher.

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• Rhyming with Proofs

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  This prompt tests an LLM's natural language and creative capabilities by prompting it to write a proof of infinitude of primes in the form of a poem.

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• Inventing New Words

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  This prompt tests an LLM's ability to create new words and use them in sentences.

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• Interdisciplinary Tasks with LLMs

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  The following prompt tests an LLM's capabilities to perform interdisciplinary tasks and showcase it's ability to generate creative and novel text.

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• Proof of Infinite Primes in Shakespeare Style

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  The following prompt tests an LLM's capabilities to write a proof that there are infinitely many primes in the style of a Shakespeare play.

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• Drawing TiKZ Diagram

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  This prompt tests an LLM's code generation capabilities by prompting it to draw a unicorn in TiKZ. In the example below the model is expected to generated the LaTeX code that can then be used to…

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• Produce MySQL Queries using LLMs

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  This prompt tests an LLM's code generation capabilities by prompting it to generate a valid MySQL query by providing information about the database schema.

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• Generate Code Snippets with LLMs

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  This prompt tests an LLM's code generation capabilities by prompting it to generate the corresponding code snippet given details about the program through a comment using / <instruction> /.

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• Sentiment Classification with LLMs

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  This prompt tests an LLM's text classification capabilities by prompting it to classify a piece of text.

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• Few-Shot Sentiment Classification with LLMs

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  This prompt tests an LLM's text classification capabilities by prompting it to classify a piece of text into the proper sentiment using few-shot examples.

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• Prompt Leaking in LLMs

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  This adversarial prompt example demonstrates the use of well-crafted attacks to leak the details or instructions from the original prompt (i.e., prompt leaking). Prompt leaking could be considered…

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• Prompt Injection in LLMs

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  This adversarial prompt example aims to demonstrate prompt injection where the LLM is originally instructed to perform a translation and an untrusted input is used to hijack the output of the model…

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• Jailbreaking LLMs

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  This adversarial prompt example aims to demonstrate the concept of jailbreaking which deals with bypassing the safety policies and guardrails of an LLM.

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