1 citations · 2 across the 9 of their papers we have counts for
9 papers
Towards Detecting Inconsistencies in End-to-end Generated TODs
Tiziano Labruna, Giovanni Bonetta, Bernardo Magnini
Generative AI is profoundly transforming the core technologies behind conversational systems, shifting from component-based to end-to-end approaches. However, Large Language Models…
eCREAM-MedCorpus A Large-Scale Corpus of Clinical Notes for Italian
Tiziano Labruna, Guido Bertolini, Pietro Ferrazzi +1
We present eCREAM-MedCorpus, a new and unique large-scale dataset of clinical notes produced in Emergency Departments of Italian hospitals. The corpus, in its current version, is c…
MALicious INTent Dataset and Inoculating LLMs for Enhanced Disinformation Detection
Arkadiusz Modzelewski, Witold Sosnowski, Eleni Papadopulos +4
The intentional creation and spread of disinformation poses a significant threat to public discourse. However, existing English datasets and research rarely address the intentional…
Detecting Winning Arguments with Large Language Models and Persuasion Strategies
Tiziano Labruna, Arkadiusz Modzelewski, Giorgio Satta +1
Detecting persuasion in argumentative text is a challenging task with important implications for understanding human communication. This work investigates the role of persuasion st…
Positional Bias in Binary Question Answering: How Uncertainty Shapes Model Preferences
Tiziano Labruna, Simone Gallo, Giovanni Da San Martino
Positional bias in binary question answering occurs when a model systematically favors one choice over another based solely on the ordering of presented options. In this study, we…
PCoT: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformation
Arkadiusz Modzelewski, Witold Sosnowski, Tiziano Labruna +2
Disinformation detection is a key aspect of media literacy. Psychological studies have shown that knowledge of persuasive fallacies helps individuals detect disinformation. Inspire…
Evaluating Task-Oriented Dialogue Consistency through Constraint Satisfaction
Tiziano Labruna, Bernardo Magnini
Task-oriented dialogues must maintain consistency both within the dialogue itself, ensuring logical coherence across turns, and with the conversational domain, accurately reflectin…
When to Retrieve: Teaching LLMs to Utilize Information Retrieval Effectively
Tiziano Labruna, Jon Ander Campos, Gorka Azkune
In this paper, we demonstrate how Large Language Models (LLMs) can effectively learn to use an off-the-shelf information retrieval (IR) system specifically when additional context…
Unraveling ChatGPT: A Critical Analysis of AI-Generated Goal-Oriented Dialogues and Annotations
Tiziano Labruna, Sofia Brenna, Andrea Zaninello +1
Large pre-trained language models have exhibited unprecedented capabilities in producing high-quality text via prompting techniques. This fact introduces new possibilities for data…