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arXiv AI By Xiazhen Wu, Wansong Qin, Yangbin Zheng, Liangda Fang, Zhan Li, Xiujie Huang, Liushen Zhou, Quanlong Guan

HANS: A Handwritten Answer Sheet Dataset for Noisy Hybrid Document Parsing

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HANS is a new handwritten answer sheet dataset designed to reflect the complexities of real‑world student submissions, including multi‑line derivations, mixed text and math, hand‑drawn tables, and noise such as strikethroughs and corrections. The dataset comes with fine‑grained annotations to support robust recognition research. Using HANS, the authors also introduce NA‑GOT, an end‑to‑end framework that applies two‑stage noise suppression and a noise‑aware attention mechanism, achieving notable gains in accuracy and stability for answer process recognition.

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 AI.

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