There is a growing trend of applying Multimodal LLMs directly to PDF pages without doing extraction first (i.e. classic RAG). We've had this request from multiple customers whose products are supposed to handle visually rich documents like "GPT for pitch decks" or "GPT for investment bankers". The problem is that you must first find the relevant page to feed into the LLM. This helps to avoid the overhead of running an expensive model on each single page.
We first attempted to extract text from pages and do a semantic/hybrid search. Still, it felt massively suboptimal since much positional information was lost, so we decided to train our model that could help with this task!