5 citations · 6 across the 8 of their papers we have counts for
10 papers
Natural Language Questions as an Interface for Knowledge Graphs: QRAKEN Graph Distillation and Semantic Self-Healing
Remo Grillo, Lukas Klic, Giovanni Colavizza
Natural-language access to RDF knowledge graphs is a core Semantic Web ambition. Large language models (LLMs) have advanced Text-to-SPARQL, yet on unfamiliar graphs they often gene…
Text Restoration of Ancient Documents with Language Models
Shibingfeng Zhang, Edoardo Caraffa, Annafelicia Zuffrano +2
Purpose - This study investigates the feasibility of restoring missing text caused by physical lacunae in damaged ancient manuscripts using language models. Methodology - The study…
EduArt: An educational-level benchmark for evaluating art history knowledge in large language models
Gianmarco Spinaci, Lukas Klic, Giovanni Colavizza
Large language models now score near ceiling on general benchmarks, but these aggregate measures reveal little about how models behave within single disciplines. Existing art-focus…
Benchmarking Large Language Models on Reference Extraction and Parsing in the Social Sciences and Humanities
Yurui Zhu, Giovanni Colavizza, Matteo Romanello
Bibliographic reference extraction and parsing are foundational for citation indexing, linking, and downstream scholarly knowledge-graph construction. However, most established eva…
Benchmarking Vision-Language and Multimodal Large Language Models in Zero-shot and Few-shot Scenarios: A study on Christian Iconography
Gianmarco Spinaci, Lukas Klic, Giovanni Colavizza
This study evaluates the capabilities of Multimodal Large Language Models (LLMs) and Vision Language Models (VLMs) in the task of single-label classification of Christian Iconograp…
Named Entity Recognition of Historical Texts via Large Language Model
Shibingfeng Zhang, Giovanni Colavizza
Large language models (LLMs) have demonstrated remarkable versatility across a wide range of natural language processing tasks and domains. One such task is Named Entity Recognitio…
Benchmarking Large Language Models for Handwritten Text Recognition
Giorgia Crosilla, Lukas Klic, Giovanni Colavizza
Traditional machine learning models for Handwritten Text Recognition (HTR) rely on supervised training, requiring extensive manual annotations, and often produce errors due to the…
Recent Developments in Deep Learning-based Author Name Disambiguation
Francesca Cappelli, Giovanni Colavizza, Silvio Peroni
Author Name Disambiguation (AND) is a critical task for digital libraries aiming to link existing authors with their respective publications. Due to the lack of persistent identifi…
An analysis of the effects of sharing research data, code, and preprints on citations
Giovanni Colavizza, Lauren Cadwallader, Marcel LaFlamme +4
Calls to make scientific research more open have gained traction with a range of societal stakeholders. Open Science practices include but are not limited to the early sharing of r…
Neural Language Models for Nineteenth-Century English
Kasra Hosseini, Kaspar Beelen, Giovanni Colavizza +1
We present four types of neural language models trained on a large historical dataset of books in English, published between 1760-1900 and comprised of ~5.1 billion tokens. The lan…