PageRank for better centrality seems neat, but it still doesn't address the probably unsolvable flaw with RAG, the reason why RAG basically can't work. All RAG DBs under-perform expectations because RAG fundamentally can't find relationships between words necessary to find the information the user cares about. Weird right, isn't this what the 'attention' mechanism is supposed to be good for? It just isn't good enough.

Example: Say you're searching an article and you want to know what occupation a mentioned person has, let's say the person 'Sharon,' is mentioned to have attended several physical chemistry conferences but her occupation is never explicitly mentioned. There's a very good chance every single rag approach will fail to return correct results, will fail to make this connection between 'occupation' attends conference, type of conference and infers 'chemist'. I could go on, but this sort of error is pervasive along all types of information when trying to retrieve with RAG. In the end, solutions like the above seem to just sort of reinvent other query methods, SQL, pagerank etc, with extra steps... there's little point in vectorization at that point...