AraMS-28k: The Largest Publicly Released Line-Level Dataset of Historical Arabic Manuscripts with Margin and Insertion-Anchor Annotations

Mohamed Guechaoui, Mohamed Diaa Zellagui, Souleyman Chaib, Sahraoui Dhelim
8/27/2026
cs.CVcs.CL

No official code found. Best implementation: ArchaText/AraMS-28k-Dataset (1 star, PyTorch, last commit 2026-07-29).

Abstract

We introduce AraMS-28k, the largest publicly released line-level dataset of genuine historical Arabic manuscripts, comprising 14 books, 3,043 pages, and 28,600 annotated text lines (27,971 main-text, 629 margin). Thirteen books are hand-copied manuscripts spanning three script traditions -- Naskh, Ruq'ah, and Maghrebi -- and one is a lithographed printed edition included to broaden format diversity. Each line is labelled as main-text or margin, and margin lines that have an unambiguous attachment point in the main text are further annotated with an insertion anchor, recovering the manuscript's true non-linear reading order at line-level granularity -- to our knowledge the first such annotation released for a historical Arabic manuscript corpus. Because reference transcriptions are fully vocalised while manuscript hands are typically undiacritised, we release both the raw diacritised transcription and a diacritic-normalised counterpart for every line. The dataset was constructed with RefLAM, a reference-grounded annotation pipeline that aligns multimodal-LLM OCR against independently sourced clean transcriptions and routes every line through human review, combining automatic verification with expert oversight. We describe the construction and quality-control process, present the annotation schema, report dataset statistics at both the corpus and per-book level, and provide baseline HTR results using Kraken and HATFormer, including a cross-script generalisation gradient from in-distribution pages to fully unseen books. AraMS-28k is released with page images, line-level annotations, and fixed train/val/test splits under CC BY-NC-SA 4.0 to support reproducible research on Arabic manuscript recognition, layout analysis, and reading-order recovery.

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PyTorch

The largest publicly released line-level dataset of historical Arabic manuscripts — 14 books, 3,043 pages, 28,600 lines, with margin/insertion-anchor annotations for non-linear reading order.

10Jul 20, 20262 months ago
arabicarabic-languagearabic-ocrbenchmarkcomputer-vision+12 more

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@article{guechaoui2026aramsk,
  title  = {AraMS-28k: The Largest Publicly Released Line-Level Dataset of Historical Arabic Manuscripts with Margin and Insertion-Anchor Annotations},
  author = {Mohamed Guechaoui and Mohamed Diaa Zellagui and Souleyman Chaib and Sahraoui Dhelim},
  year   = {2026},
  eprint = {2608.26921},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2608.26921v1}
}

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