6 papers
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…
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 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…
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…