arXiv Machine Learning
EMBLEM: Enhancing Multi-script Table Detection through Masking
Read the original on arXiv Machine Learning →The Flow has not summarised this story yet — read it at arXiv Machine Learning.
Related stories
arXiv Computer Vision
Sep 22
All-in-One Multilingual Scene Text Recognition with Script-aware Mixture-of-Experts
The paper introduces an all‑in‑one multilingual scene text recognizer called ScriptMoE, which uses a script‑aware mixture‑of‑experts architecture to handle 10 scripts and 229 languages. It is built on a new large‑scale synthetic dataset, TextMuSS‑10M, and evaluated on the TextMuSS‑Bench, achieving 82.06% accuracy—1.31% higher than the best baseline. When integrated into the PP‑OCRv5 pipeline, ScriptMoE raises the end‑to‑end multilingual F1 score from 65.71% to 80.89%, slightly surpassing the best vision‑language model while using far fewer parameters.
arXiv Computation and Language
2d ago
From Zero to OCR: A Data-Centric Framework for Unsupported Low-Resource Scripts
The paper introduces a data‑centric framework that enables end‑to‑end OCR for low‑resource scripts using only an unannotated text corpus and digital fonts, eliminating the need for manually annotated training images. A synthetic data engine generates realistic word, line, and page images with accurate script shaping, which are then used to train a YOLOv8 word detector and a convolutional recurrent recognizer via connectionist temporal classification. Applied to the Kashmiri Perso‑Arabic Nastaliq script, the system achieves a 0.39% character error rate on held‑out words and provides publicly released models, code, and a synthetic dataset of 285,864 text‑line images.
Hugging Face Trending Papers
Sep 15
Tables Decoded: DELTA for Structure, TARQA for Understanding
Table understanding is a core task in document intelligence, encompassing two key subtasks: table reconstruction and table visual question answering (TabVQA). While recent approaches predominantly rel...
arXiv Computer Vision
1d ago
PubTables-v2: A new large-scale dataset for full-page and multi-page table extraction
arXiv:2512.10888v4 Announce Type: replace Abstract: Table extraction (TE) is a key challenge in document understanding. Traditional approaches detect tables first, then recognize their structure. Rec...
Hugging Face Trending Papers
Aug 19
Impact of Iterative Fine-Tuning on Transcription Accuracy in Complex Historical Sanskrit Manuscripts
The paper presents a local traditional OCR pipeline that can be iteratively fine‑tuned on both layout and appearance levels of complex historical Sanskrit manuscripts. By adapting to the specific manuscript distribution, the pipeline improves transcription accuracy across subsequent pages, reducing the need for costly human annotation. The authors apply the method to three manuscripts, release a dataset with detailed layout and Unicode annotations in PAGE‑XML format, and benchmark the results against leading multimodal large language models.
arXiv AI
Aug 20
Impact of Iterative Fine-Tuning on Transcription Accuracy in Complex Historical Sanskrit Manuscripts
The paper presents a local traditional OCR pipeline that can be iteratively fine‑tuned on both layout and appearance levels of complex historical Sanskrit manuscripts. By adapting to the specific manuscript distribution, the pipeline reduces human annotation effort and improves transcription accuracy across subsequent pages. The authors apply this method to three manuscripts, release a dataset with detailed layout and Unicode annotations in PAGE‑XML format, and benchmark the pipeline against leading multimodal large language models.