Document-as-Image Representations Fall Short for Scientific Retrieval
Current document embedding models rely on treating documents as images of rendered pages, which is inefficient for complex scientific texts containing text, tables, and figures. The authors introduce ArXivDoc, a new benchmark built from raw LaTeX sources. Comparing text-only, image-based, and multimodal representations shows that interleaved text+image methods outperform image-based approaches without extra training.