Source: thenewstack.io
How to Reduce the Hallucinations from Large Language Models
In the https://thenewstack.io/prompt-engineering-get-llms-to-generate-the-content-you-want/ of this series, we have seen various types of prompts to extract the expected outcome from large language models. In this article, we will explore the techniques to reduce hallucinations in the output of large language models (LLMs).
In the world of Large Language Models, the term hallucination refers to the tendency of the models to produce text that appears to be correct but is actually false or not based on the input given.
Consider feeding the Large Language Model with the following prompt: “Describe the impact of Adolf Hitler’s moon landing.”
Context injection is a technique used to improve the performance of large language models (LLMs) by providing them with additional information that supplements the prompt.
In the world of Large Language Models, the term hallucination refers to the tendency of the models to produce text that appears to be correct but is actually false or not based on the input given.
Consider feeding the Large Language Model with the following prompt: “Describe the impact of Adolf Hitler’s moon landing.”
Context injection is a technique used to improve the performance of large language models (LLMs) by providing them with additional information that supplements the prompt.
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