
Prompt Engineering How To: Reducing Hallucinations in Prompt Responses for LLMs
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The episode explains how AI language models can mitigate hallucinations - the generation of false information - through prompt engineering strategies and reinforced training techniques. It describes methods like providing context, setting constraints, requiring citations, and giving examples to guide models toward factual responses. Benchmark datasets like TruthfulQA are essential for evaluating model hallucination tendencies. With thoughtful prompting and training, language models can become less prone to fabrication and provide users with truthful, reliable information rather than misleading them through hallucinations.
Blog Post:
https://blog.cprompt.ai/prompt-engineering-how-to-reducing-hallucinations-in-prompt-responses-for-llms
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