Up to 36x Speedup: Mask-based Parallel Inference Paradigm for Key Information Extraction in MLLMs

• URL: http://arxiv.org/abs/2601.19613v1
• Date: Tue, 27 Jan 2026 13:45:30 GMT
• Title: Up to 36x Speedup: Mask-based Parallel Inference Paradigm for Key Information Extraction in MLLMs
• Authors: Xinzhong Wang, Ya Guo, Jing Li, Huan Chen, Yi Tu, Yijie Hong, Gongshen Liu, Huijia Zhu,
• Abstract summary: We introduce PIP: a Parallel Inference Paradigm for Key Information Extraction (KIE)<n>Our approach reformulates the problem by using "[mask]" tokens as placeholders for all target values, enabling their simultaneous generation in a single forward pass.<n> Experimental results show that our PIP-models achieve a 5-36x inference speedup with negligible performance degradation compared to traditional autoregressive base models.
• Score: 22.76757502541604
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Key Information Extraction (KIE) from visually-rich documents (VrDs) is a critical task, for which recent Large Language Models (LLMs) and Multi-Modal Large Language Models (MLLMs) have demonstrated strong potential. However, their reliance on autoregressive inference, which generates outputs sequentially, creates a significant efficiency bottleneck, especially as KIE tasks often involve extracting multiple, semantically independent fields. To overcome this limitation, we introduce PIP: a Parallel Inference Paradigm for KIE. Our approach reformulates the problem by using "[mask]" tokens as placeholders for all target values, enabling their simultaneous generation in a single forward pass. To facilitate this paradigm, we develop a tailored mask pre-training strategy and construct large-scale supervised datasets. Experimental results show that our PIP-models achieve a 5-36x inference speedup with negligible performance degradation compared to traditional autoregressive base models. By substantially improving efficiency while maintaining high accuracy, PIP paves the way for scalable and practical real-world KIE solutions.

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