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This study from August 2023 considers 10 different prompt techniques, over six LLMs and six data types.

Large Language Models (LLMs) are known to hallucinate. Hallucination is when a LLM generates a highly succinct and highly plausible answer; but factually incorrect. Hallucination can be negated by injecting prompts with contextually relevant data which the LLM can reference.

And how to manage the performance and cost of large context input to LLMs.

In this article I consider the growing context of various Large Language Models (LLMs) to what extent it can be used and how a principle like RAG applies.