12 citations · 21 across the 12 of their papers we have counts for
15 papers
DeskForge: Dense Supervision from Desktop Environments for Computer-Use Agents
A. Said Gurbuz, Ahmed Nassar, Sunghwan Hong +2
Computer-use agents need to reliably ground action targets in complex desktop scenes, where multiple applications, overlapping windows, and visually similar controls compete for at…
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…
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…
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…
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…
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…
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…
ChartGen: Scaling Chart Understanding Via Code-Guided Synthetic Chart Generation
Jovana Kondic, Pengyuan Li, Dhiraj Joshi +12
Chart-to-code reconstruction -- the task of recovering executable plotting scripts from chart images -- provides important insights into a model's ability to ground data visualizat…
MarkushGrapher: Joint Visual and Textual Recognition of Markush Structures
Lucas Morin, Valéry Weber, Ahmed Nassar +4
The automated analysis of chemical literature holds promise to accelerate discovery in fields such as material science and drug development. In particular, search capabilities for…
SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion
Ahmed Nassar, Andres Marafioti, Matteo Omenetti +10
We introduce SmolDocling, an ultra-compact vision-language model targeting end-to-end document conversion. Our model comprehensively processes entire pages by generating DocTags, a…
Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence
Granite Vision Team, Leonid Karlinsky, Assaf Arbelle +60
We introduce Granite Vision, a lightweight large language model with vision capabilities, specifically designed to excel in enterprise use cases, particularly in visual document un…
Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion
Nikolaos Livathinos, Christoph Auer, Maksym Lysak +14
We introduce Docling, an easy-to-use, self-contained, MIT-licensed, open-source toolkit for document conversion, that can parse several types of popular document formats into a uni…
Docling Technical Report
Christoph Auer, Maksym Lysak, Ahmed Nassar +16
This technical report introduces Docling, an easy to use, self-contained, MIT-licensed open-source package for PDF document conversion. It is powered by state-of-the-art specialize…
KVP10k : A Comprehensive Dataset for Key-Value Pair Extraction in Business Documents
Oshri Naparstek, Roi Pony, Inbar Shapira +15
In recent years, the challenge of extracting information from business documents has emerged as a critical task, finding applications across numerous domains. This effort has attra…
ESG Accountability Made Easy: DocQA at Your Service
Lokesh Mishra, Cesar Berrospi, Kasper Dinkla +11
We present Deep Search DocQA. This application enables information extraction from documents via a question-answering conversational assistant. The system integrates several techno…