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arXiv Computer Vision By Hao Yu, Kang Liu, Linnan Zhao, Jiabo Zhan, Chong Sun, Chen Li, Jing Lyu

WeVisDoc: From Coverage to Capability for Robust End-to-End Document Parsing

Read the original on arXiv Computer Vision →

WeVisDoc is a two‑stage data‑centric framework designed to improve end‑to‑end document parsing. Stage I expands coverage by adding heterogeneous data and applying structure‑preserving degradation synthesis, while Stage II evaluates residual errors with a held‑out probe and uses those diagnostics to target data construction and token budget reallocation. The resulting WeVisDoc‑4B model achieves an overall score of 95.38 on OmniDocBench v1.6 and outperforms competing parsers across all evaluated settings, with Stage II delivering notable gains on degraded tracks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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