12 citations · 32 across the 6 of their papers we have counts for
6 papers
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…
Statements: Universal Information Extraction from Tables with Large Language Models for ESG KPIs
Lokesh Mishra, Sohayl Dhibi, Yusik Kim +4
Environment, Social, and Governance (ESG) KPIs assess an organization's performance on issues such as climate change, greenhouse gas emissions, water consumption, waste management,…
INDUS: Effective and Efficient Language Models for Scientific Applications
Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka +33
Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs tr…
Otter-Knowledge: benchmarks of multimodal knowledge graph representation learning from different sources for drug discovery
Hoang Thanh Lam, Marco Luca Sbodio, Marcos Martínez Galindo +6
Recent research on predicting the binding affinity between drug molecules and proteins use representations learned, through unsupervised learning techniques, from large databases o…
Delivering Document Conversion as a Cloud Service with High Throughput and Responsiveness
Christoph Auer, Michele Dolfi, André Carvalho +2
Document understanding is a key business process in the data-driven economy since documents are central to knowledge discovery and business insights. Converting documents into a ma…