Author

Yonghui Wang

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Preprint Jul 2026

Hierarchical Evidence-Driven Reasoning for Long Document Understanding

HIEVI-RAG is introduced, a hierarchical, evidence-driven multimodal RAG framework for closed-domain document understanding that significantly outperforms existing open-source baselines and exceeds the strongest reported baseline by an average of 8.05% in accuracy.

Junyu Xiong, Yonghui Wang, Rongjian Gu et al. · 1 citation

Preprint Jul 2026

HierDoc: Hierarchical Page-to-Region Evidence Routing for Long-Document Visual Question Answering

HierDoc, a hierarchical evidence-routing framework that formulates long-document evidence acquisition as two-stage set prediction from pages to regions, achieves state-of-the-art or competitive performance among open-weight systems, improving LongDocURL by 16.87% relative to the strongest reported open-weight baseline.

Rongjian Gu, Weng Zhou, Junyu Xiong et al. · 0 citations