Comment by stared
4 days ago
It is up for testing, but you likely get the effect of "don't think about a pink elephant." So I guess that for most embedding models, "articles about San Francisco that don't mention cars" are closest to articles about SF that mention cars.
The fundamental issue here is comparing apples to oranges, questions, and answers.
So is LLM pre/post-processing the best approach here?