28 citations · 49 across the 7 of their papers we have counts for
10 papers
Towards Hierarchical Structure Understanding of Newspaper Images
William Mocaër, Solène Tarride, Thomas Constum +7
Understanding newspaper images remains a challenging task due to their complex, nested hierarchical structures and dense, heterogeneous layouts. In this paper, we explore two compl…
Scaling State-Space Models from Lines to Paragraphs: An Ablation of Mamba-based OCR
Merveilles Agbeti-Messan, Pierrick Tranouez, Stéphane Nicolas +2
End-to-end OCR increasingly relies on autoregressive sequence models, where the quadratic cost of Transformer attention limits efficient transcription of long, paragraph-level text…
A Benchmark of State-Space Models vs. Transformers and BiLSTM-based Models for Historical Newspaper OCR
Merveilles Agbeti-Messan, Pierrick Tranouez, Stéphane Nicolas +2
End-to-end OCR for historical newspapers remains challenging, as models must handle long text sequences, degraded print quality, and complex layouts. While Transformer-based recogn…
Few-shot Writer Adaptation via Multimodal In-Context Learning
Tom Simon, Stephane Nicolas, Pierrick Tranouez +2
While state-of-the-art Handwritten Text Recognition (HTR) models perform well on standard benchmarks, they frequently struggle with writers exhibiting highly specific styles that a…
Classifying the Unknown: In-Context Learning for Open-Vocabulary Text and Symbol Recognition
Tom Simon, William Mocaer, Pierrick Tranouez +2
We introduce Rosetta, a multimodal model that leverages Multimodal In-Context Learning (MICL) to classify sequences of novel script patterns in documents by leveraging minimal exam…
Dynamic Graph Representation Learning with Neural Networks: A Survey
Leshanshui Yang, Sébastien Adam, Clément Chatelain
In recent years, Dynamic Graph (DG) representations have been increasingly used for modeling dynamic systems due to their ability to integrate both topological and temporal informa…