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Jeff Tang

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#small language model Preprint Sep 2026

DocMIDE: Learning Multi-Hop Implicit Derivation in Visually Rich Documents

DocMIDE is introduced, a fine-tuning framework that trains compact vision-language models to retrieve visual evidence explicitly before deriving an answer, and constrains generation to a plan-retrieve-derive structure and optimizes it with Group Relative Policy Optimization under a four-component, rule-based reward.

Jeremy Cerwin Wang, Wai-Kit Wong, Jeff Tang · 0 citations