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20212026
most citedNamed entity recognition architecture combining contextual and global features

17 citations · 20 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Video Transformer for Remote Identity Document Hologram Detection

Joris Voerman, Nicolas Sidere, Jean-Christophe Burie

Remote identity authentification using Identification Documents has been a major challenge for several years. DeepFakes advent and the development of AI-guided tools helps fraudste…

cs.CV2026

DocQT: Improving Document Forgery Localization Robustness via Diverse JPEG Quantization Tables

Kylian Ronfleux-Corail, Guillaume Bernard, Mickaël Coustaty +1

Document manipulation localization models achieve strong performance on public benchmarks yet fail to generalize to operational document workflows. We identify a critical and overl…

cs.CL2024

CoastTerm: a Corpus for Multidisciplinary Term Extraction in Coastal Scientific Literature

Julien Delaunay, Hanh Thi Hong Tran, Carlos-Emiliano González-Gallardo +6

The growing impact of climate change on coastal areas, particularly active but fragile regions, necessitates collaboration among diverse stakeholders and disciplines to formulate e…

cs.CV2024

IDTrust: Deep Identity Document Quality Detection with Bandpass Filtering

Musab Al-Ghadi, Joris Voerman, Souhail Bakkali +3

The increasing use of digital technologies and mobile-based registration procedures highlights the vital role of personal identity documents (IDs) in verifying users and safeguardi…

cs.CL2023★ 3 cited

A Comprehensive Survey of Document-level Relation Extraction (2016-2023)

Julien Delaunay, Hanh Thi Hong Tran, Carlos-Emiliano González-Gallardo +3

Document-level relation extraction (DocRE) is an active area of research in natural language processing (NLP) concerned with identifying and extracting relationships between entiti…

cs.CL2021★ 17 cited

Named entity recognition architecture combining contextual and global features

Tran Thi Hong Hanh, Antoine Doucet, Nicolas Sidere +2

Named entity recognition (NER) is an information extraction technique that aims to locate and classify named entities (e.g., organizations, locations,...) within a document into pr…