MegaRAG: Multimodal Knowledge Graph-Based Retrieval Augmented Generation

ArXi:2512.20626v2 Announce Type: replace-cross Retrieval-augmented generation (RAG) enables large language models (LLMs) to dynamically access external information, which is powerful for answering questions over previously unseen documents. Nonetheless, they struggle with high-level conceptual understanding and holistic comprehension due to limited context windows, which constrain their ability to perform deep reasoning over long-form, domain-specific content such as full-length books.