544 citations · 727 across the 12 of their papers we have counts for
13 papers
GPT Assisted Annotation of Rhetorical and Linguistic Features for Interpretable Propaganda Technique Detection in News Text
Kyle Hamilton, Luca Longo, Bojan Bozic
While the use of machine learning for the detection of propaganda techniques in text has garnered considerable attention, most approaches focus on "black-box" solutions with opaque…
CNN-based explanation ensembling for dataset, representation and explanations evaluation
Weronika Hryniewska-Guzik, Luca Longo, Przemysław Biecek
Explainable Artificial Intelligence has gained significant attention due to the widespread use of complex deep learning models in high-stake domains such as medicine, finance, and…
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions
Luca Longo, Mario Brcic, Federico Cabitza +16
As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In respo…
A novel structured argumentation framework for improved explainability of classification tasks
Lucas Rizzo, Luca Longo
This paper presents a novel framework for structured argumentation, named extend argumentative decision graph (). It is an extension of argumentative decision graphs built up…
Modeling cognitive load as a self-supervised brain rate with electroencephalography and deep learning
Luca Longo
The principal reason for measuring mental workload is to quantify the cognitive cost of performing tasks to predict human performance. Unfortunately, a method for assessing mental…
Comparing and extending the use of defeasible argumentation with quantitative data in real-world contexts
Lucas Rizzo, Luca Longo
Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapte…
An Evaluation of the EEG alpha-to-theta and theta-to-alpha band Ratios as Indexes of Mental Workload
Bujar Raufi, Luca Longo
Many research works indicate that EEG bands, specifically the alpha and theta bands, have been potentially helpful cognitive load indicators. However, minimal research exists to va…
Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Review
Kyle Hamilton, Aparna Nayak, Bojan Božić +1
Advocates for Neuro-Symbolic Artificial Intelligence (NeSy) assert that combining deep learning with symbolic reasoning will lead to stronger AI than either paradigm on its own. As…
Weakly Complete Semantics Based on Undecidedness Blocking
Pierpaolo Dondio, Luca Longo
In this paper we introduce a novel family of semantics called weakly complete semantics. Differently from Dung's complete semantics, weakly complete semantics employs a mechanism c…
Explainable Artificial Intelligence: a Systematic Review
Giulia Vilone, Luca Longo
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few years. This is due to the widespread application of machine learning, particularly…
Expressing Trust with Temporal Frequency of User Interaction in Online Communities
Ekaterina Yashkina, Arseny Pinigin, JooYoung Lee +4
Reputation systems concern soft security dynamics in diverse areas. Trust dynamics in a reputation system should be stable and adaptable at the same time to serve the purpose. Many…
Towards dynamic interaction-based model
Almaz Melnikov, Manuel Mazzara, Victor Rivera +2
In this paper, we investigate how dynamic properties of reputation can influence the quality of users ranking. Reputation systems should be based on rules that can guarantee a high…
Pseudorehearsal in actor-critic agents with neural network function approximation
Vladimir Marochko, Leonard Johard, Manuel Mazzara +1
Catastrophic forgetting has a significant negative impact in reinforcement learning. The purpose of this study is to investigate how pseudorehearsal can change performance of an ac…