I've not followed the literature very closely for some time - what problem are they trying to solve in the first place? They write "for documents to be effectively used in RAG pipelines, they must be split into smaller, semantically meaningful chunks". Segmenting each page by paragraphs doesn't seem like a particularly hard vision problem, nor do I see why an OCR system would need to incorporate an LLM (which seem more like a demonstration of overfitting than a "language model" in any literal sense, going by ChatGPT). Perhaps I'm just out of the loop.
Finally, I must point out that statements in the vein of "Why [product] 2.0 Changes Everything" are more often than not a load of humbug.
Finally, I must point out that statements in the vein of "Why [product] 2.0 Changes Everything" are more often than not a load of humbug.