activity
20222025
most citedLocalising In-Domain Adaptation of Transformer-Based Biomedical Language Models

28 citations · 57 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2025

RAR: Setting Knowledge Tripwires for Retrieval Augmented Rejection

Tommaso Mario Buonocore, Enea Parimbelli

Content moderation for large language models (LLMs) remains a significant challenge, requiring flexible and adaptable solutions that can quickly respond to emerging threats. This p…

cs.LG2024

Introducing δ-XAI: a novel sensitivity-based method for local AI explanations

Alessandro De Carlo, Enea Parimbelli, Nicola Melillo +1

Explainable Artificial Intelligence (XAI) is central to the debate on integrating Artificial Intelligence (AI) and Machine Learning (ML) algorithms into clinical practice. High-per…

cs.CL2024★ 1 cited

Igea: a Decoder-Only Language Model for Biomedical Text Generation in Italian

Tommaso Mario Buonocore, Simone Rancati, Enea Parimbelli

The development of domain-specific language models has significantly advanced natural language processing applications in various specialized fields, particularly in biomedicine. H…

cs.CL2024★ 17 cited

Reshaping Free-Text Radiology Notes Into Structured Reports With Generative Transformers

Laura Bergomi, Tommaso M. Buonocore, Paolo Antonazzo +5

BACKGROUND: Radiology reports are typically written in a free-text format, making clinical information difficult to extract and use. Recently the adoption of structured reporting (…

cs.LG2024★ 2 cited

Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple Sclerosis

Lorenzo Peracchio, Giovanna Nicora, Enea Parimbelli +5

Applying Artificial Intelligence (AI) and Machine Learning (ML) in critical contexts, such as medicine, requires the implementation of safety measures to reduce risks of harm in ca…

cs.CL2023★ 9 cited

Advancing Italian Biomedical Information Extraction with Transformers-based Models: Methodological Insights and Multicenter Practical Application

Claudio Crema, Tommaso Mario Buonocore, Silvia Fostinelli +10

The introduction of computerized medical records in hospitals has reduced burdensome activities like manual writing and information fetching. However, the data contained in medical…

cs.CL2022★ 28 cited

Localising In-Domain Adaptation of Transformer-Based Biomedical Language Models

Tommaso Mario Buonocore, Claudio Crema, Alberto Redolfi +2

In the era of digital healthcare, the huge volumes of textual information generated every day in hospitals constitute an essential but underused asset that could be exploited with…