Gianluca Moro

Learning Interpretable and Statistically Significant Knowledge from Unlabeled Corpora of Social Text Messages: A Novel Methodology of Descriptive Text Mining

2020

Though the strong evolution of knowledge learning models has characterized the last few years, the explanation of a phenomenon from text documents, called descriptive text mining, is still a difficult and poorly addressed problem. The …

Semantic Self-Segmentation for Abstractive Summarization of Long Documents in Low-Resource Regimes

2022 · Proceedings of the AAAI Conference on Artificial Intelligence

The quadratic memory complexity of transformers prevents long document summarization in low computational resource scenarios. State-of-the-art models need to apply input truncation, thus discarding and ignoring potential summary-relevant contents, leading to a performance drop. Furthermore, …

OpenBioNER: Lightweight Open-Domain Biomedical Named Entity Recognition Through Entity Type Description

2025

Biomedical Named Entity Recognition (BioNER) faces significant challenges in real-world applications due to limited annotated data and the constant emergence of new entity types, making zero-shot learning capabilities crucial.While Large Language Models (LLMs) possess extensive …