Instead of checking for exact words, how would you use BERTScore or Cosine Similarity of embeddings to evaluate if an LLM's summary is accurate?

Why is a standard unit test (asserting that output == "expected") often a bad way to test an LLM? How do you handle a model that gives three different, but correct, answers to the same prompt?

How do you programmatically check if an LLM is making things up that aren't in the provided search results?

If you are using an LLM to grade another LLM, why is it critical to provide a "multi-point rubric" rather than just asking "Is this answer good?"