most citedVDocRAG: Retrieval-Augmented Generation over Visually-Rich Documents

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cs.CL2025

Instruction-Following Evaluation of Large Vision-Language Models

Daiki Shiono, Shumpei Miyawaki, Ryota Tanaka +1

Following the initial flourishing of large language models (LLMs), there has been a surge in proposed large vision-language models (LVLMs) that integrate LLMs with vision capabilit…

cs.CL2025★ 2 cited

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…