VDocRAG: Retrieval-Augmented Generation over Visually-Rich Documents

Ryota Tanaka, Taichi Iki, Taku Hasegawa +3

We aim to develop a retrieval-augmented generation (RAG) framework that answers questions over a corpus of visually-rich documents presented in mixed modalities (e.g., charts, tabl…