575 citations · 880 across the 16 of their papers we have counts for
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cs.AI2026
It's All in the Way You Say It: The Role of Information Representation in LLM-Based Glycemic-Event Prediction
Andrea Apicella, Pasquale Arpaia, Matteo Orefice +2
Large Language Models (LLMs) are increasingly being investigated for physiological time-series prediction, yet their effectiveness may depend not only on the model itself, but also…
cs.AI2023★ 1 cited
Strategies to exploit XAI to improve classification systems
Andrea Apicella, Luca Di Lorenzo, Francesco Isgrò +2
Explainable Artificial Intelligence (XAI) aims to provide insights into the decision-making process of AI models, allowing users to understand their results beyond their decisions.…