100% accuracy isn’t every thing: serving to customers navigate the doc is the true worth
So, you’re constructing a RAG system or utilizing an LLM to talk with paperwork. However customers usually ask: how can we belief the solutions?
Furthermore, we often hear about hallucinations, which undermine customers’ belief.
If we construct an utility however fail to point out customers the place the solutions come from, the appliance may turn out to be unusable in some instances.
On this article, I’ll share an method to handle this concern. By linking each reply generated by the LLM to its supply textual content within the doc, we will construct transparency and belief. This methodology not solely offers clear proof for the solutions but in addition permits customers to confirm the outcomes instantly inside the PDF.
Generally, the generated reply will not be completely correct, however having the ability to find the proper supply textual content is already useful for the person.
Let’s take an instance of this paper from arxiv.org. We will think about this use case:
Step one on this method is to extract the textual content from the PDF in a structured format.
