MARDoc framework enhances multimodal long document QA with structured memory

Researchers have introduced MARDoc, a new framework designed to improve question-answering capabilities for long, multimodal documents. MARDoc utilizes three specialized agents—Explorer, Refiner, and Reflector—to manage retrieval, memory distillation, and evidence checking. This approach separates interaction traces into structured memories, reducing context noise and enhancing multi-hop reasoning accuracy compared to systems that maintain a single, accumulating context. Experiments on benchmark datasets demonstrate MARDoc's effectiveness in outperforming existing methods. AI

IMPACT Introduces a novel agentic framework that could improve how AI systems process and answer questions from extensive, multimodal documents.

RANK_REASON The cluster contains a research paper detailing a new framework for multimodal long document question answering. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

• arXiv

• paper
• model release

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →