32 citations · 55 across the 6 of their papers we have counts for
3 papers · 1 filter
Towards Reliable and Interpretable Document Question Answering via VLMs
Alessio Chen, Simone Giovannini, Andrea Gemelli +2
Vision-Language Models (VLMs) have shown strong capabilities in document understanding, particularly in identifying and extracting textual information from complex documents. Despi…
BoundingDocs: a Unified Dataset for Document Question Answering with Spatial Annotations
Simone Giovannini, Fabio Coppini, Andrea Gemelli +1
We present a unified dataset for document Question-Answering (QA), which is obtained combining several public datasets related to Document AI and visually rich document understandi…
CTE: A Dataset for Contextualized Table Extraction
Andrea Gemelli, Emanuele Vivoli, Simone Marinai
Relevant information in documents is often summarized in tables, helping the reader to identify useful facts. Most benchmark datasets support either document layout analysis or tab…