1 citations · 1 across the 5 of their papers we have counts for
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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…
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…
ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, Pengyuan Li, Dhiraj Joshi +24
Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a capability where current vision-language…
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…
SubGrapher: Visual Fingerprinting of Chemical Structures
Lucas Morin, Gerhard Ingmar Meijer, Valéry Weber +2
Automatic extraction of chemical structures from scientific literature plays a crucial role in accelerating research across fields ranging from drug discovery to materials science.…
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…