Română(RO) MAGE-RAG: Multigranular Adaptive Graph Evidence for Agentic Multimodal RAG in Long-Document QA

MAGE-RAG 框架增强长文档的多模态问答能力

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-14 16:34

研究人员推出 MAGE-RAG，一个旨在改进长文档多模态问答的新框架。该系统构建了一个自适应证据图，整合了文本、图像、表格和布局信息。在查询时，证据控制器动态选择和修剪相关信息，为大型语言模型创建紧凑、结构化的输入，从而平衡证据覆盖率和噪声抑制。 AI

影响该框架可以改进 AI 系统处理和回答包含混合媒体的复杂长文档中问题的能力。

排序理由该集群包含一篇详细介绍多模态问答新框架的研究论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

报道来源 [2]

arXiv cs.AI TIER_1 Română(RO) · Yilong Zuo, Xunkai Li, Jing Yuan, Qiangqiang Dai, Hongchao Qin, Ronghua Li · 2026-06-16 04:00

MAGE-RAG: Multigranular Adaptive Graph Evidence for Agentic Multimodal RAG in Long-Document QA

arXiv:2606.15906v1 Announce Type: cross Abstract: Long-document multimodal question answering requires a system to locate sparse evidence in long PDFs and integrate clues from text, tables, images, charts, and complex layouts. Existing RAG methods mostly rely on fixed Top-k retri…
arXiv cs.IR (Information Retrieval) TIER_1 Română(RO) · Ronghua Li · 2026-06-14 16:34

MAGE-RAG: Multigranular Adaptive Graph Evidence for Agentic Multimodal RAG in Long-Document QA

Long-document multimodal question answering requires a system to locate sparse evidence in long PDFs and integrate clues from text, tables, images, charts, and complex layouts. Existing RAG methods mostly rely on fixed Top-k retrieval over text chunks or pages. Text retrieval can…