activity
20242026
collaborators

13 papers

cs.CV2026

Identify, Locate, Link: End-to-End Key-Value Extraction from Document Images

A. Said Gurbuz, Ahmed Nassar, Christoph Auer +8

Document processing pipelines traditionally cascade optical character recognition (OCR) engines with downstream models for structured information extraction, leading to multi-stage…

cs.CL2026

DocAtlas: Multilingual Document Understanding Across 80+ Languages

Ahmed Heakl, Youssef Mohamed, Abdullah Sohail +6

Multilingual document understanding remains limited for low-resource languages due to scarce training data and model-based annotation pipelines that perpetuate existing biases. We…

cs.CV2026

Structured Layout Priors for Robust Out-of-Distribution Visual Document Understanding

Peter El Hachem, Ahmed Nassar, A. Said Gurbuz +2

Vision-Language Models (VLMs) parse documents end-to-end but frequently break down on layouts unlike those seen in training. We attribute this to a two-hop bottleneck: before the d…

cs.CV2026

ScreenParse: Moving Beyond Sparse Grounding with Complete Screen Parsing Supervision

A. Said Gurbuz, Sunghwan Hong, Ahmed Nassar +2

Modern computer-use agents (CUA) must perceive a screen as a structured state, what elements are visible, where they are, and what text they contain, before they can reliably groun…

cs.CV2026

MarkushGrapher-2: End-to-end Multimodal Recognition of Chemical Structures

Tim Strohmeyer, Lucas Morin, Gerhard Ingmar Meijer +3

Automatically extracting chemical structures from documents is essential for the large-scale analysis of the literature in chemistry. Automatic pipelines have been developed to rec…

cs.CV2025

Advanced Layout Analysis Models for Docling

Nikolaos Livathinos, Christoph Auer, Ahmed Nassar +16

This technical report documents the development of novel Layout Analysis models integrated into the Docling document-conversion pipeline. We trained several state-of-the-art object…