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HPD-Parsing introduces a hierarchical parallel decoding paradigm for VLM-based document parsing, replacing full-page autoregressive generation to achieve 4,752 tokens per second throughput (2.62x faster than prior models) while maintaining competitive accuracy.
MM-BizRAG is a multimodal retrieval-augmented generation system for enterprise Q&A that uses document structure-aware splitting and layout-aware parsing to outperform vision-centric baselines by up to 32% on heterogeneous enterprise documents. The paper also introduces FastRAGEval, a cost-efficient LLM-based evaluation metric with stronger human alignment than RAGChecker.
MinerU2.5 is a 1.2B-parameter vision-language model that achieves state-of-the-art document parsing accuracy with high computational efficiency using a coarse-to-fine parsing strategy.