LLMs are known for hallucinations and we went through the works and papers to condense the what, the why and the hows of mitigating hallucinations.
- Discover why even the best of the best LLMs sometimes just "make stuff up."
- Learn the main culprits behind hallucinations—bad data, flawed prompts, and more.
- Understand the four major hallucination types and how they impact AI output.
- Find out how to measure AI trustworthiness—benchmarks, entropy, and other tools.
- Implement foolproof methods to prevent hallucinations—better prompts, reciprocity, fine-tuning, and more.
- Discover SAR, a metric that accurately tells if any LLM is hallucinating 70% of the time without any prior setup
- See how asking your LLM to "explain itself" can lead to more reliable answers.
- Explore how to use confidence scores to make your LLM smarter.
- Techniques in document extraction that prevent AI from "making things up."
https://nanonets.com/blog/how-to-tell-if-your-llm-is-hallucinating/
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