AI VS hallucination-leaderboard

Code for this article is available here and here , but as always I would suggest you to please read the full article for better understanding.

To checkout the Hallucination leaderboard click here

Nice to see yet another open source approach to LLM/RAG. For those who do not want to meddle with the complexity of do-it-youself, Vectara (https://vectara.com) provides a RAG-as-a-service approach - pretty helpful if you want to stay away from having to worry about all the details, scalability, security, etc - and just focus on building your RAG application.

Check this leaderboard, it is specific for RAG use case: https://github.com/vectara/hallucination-leaderboard

You should also check us out (https://vectara.com) - we provide RAG as a service so you don't have to do all the heavy lifting and putting together the pieces yourself.

Llama 2 (and variants). Has the lowest hallucination rate (https://github.com/vectara/hallucination-leaderboard), and its open source and so we know what went into it, and the community can improve it

This is just typical of so much work in the field. They pick and choose which models to compare against and on which benchmarks. If this model was truly great, they would be comparing against Claude 2 and GPT4 across a bunch of different benchmarks. Instead they compare against Palm 2, which in a lot of tests is a weak model (https://venturebeat.com/ai/google-bard-fails-to-deliver-on-i....) and prone to hallucination (https://github.com/vectara/hallucination-leaderboard).