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Fosca Giannotti

4 accepted papers

2025

Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts

Andrea Pugnana, Riccardo Massidda, Francesco Giannini, Pietro Barbiero, Mateo Espinosa Zarlenga, Roberto Pellungrini +3
NeurIPS 2025poster

Concept Bottleneck Models (CBMs) are interpretable machine learning models that ground their predictions on human-understandable concepts, allowing for targeted interventions in their decision-making process. However, when intervened on, CBMs assume the availability of humans that can identify the n…

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2025

Human-AI Coevolution (Abstract Reprint)

Dino Pedreschi, Luca Pappalardo, Emanuele Ferragina, Ricardo Baeza-Yates, Albert-László Barabási, Frank Dignum +11
IJCAI 2025

Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artificial intelligence and complexity science literature. Recommender systems and assistants play a prominent role in human-

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2025

Perspectives in Play: A Multi-Perspective Approach for More Inclusive NLP Systems

Benedetta Muscato, Lucia Passaro, Gizem Gezici, Fosca Giannotti
IJCAI 2025

In the realm of Natural Language Processing (NLP), common approaches for handling human disagreement consist of aggregating annotators' viewpoints to establish a single ground truth. However, prior studies show that disregarding individual opinions can lead to the side-effect of under-representing m

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2023

HANSEN: Human and AI Spoken Text Benchmark for Authorship Analysis

Nafis Irtiza Tripto, Adaku Uchendu, Thai Le, Mattia Setzu, Fosca Giannotti, Dongwon Lee
EMNLP 2023long findings

$\textit{Authorship Analysis}$, also known as stylometry, has been an essential aspect of Natural Language Processing (NLP) for a long time. Likewise, the recent advancement of Large Language Models (LLMs) has made authorship analysis increasingly crucial for distinguishing between human-written and…

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