Papers by Lorenzo Gatti
What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric (2023.acl-long)
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Enrico Liscio, Oscar Araque, Lorenzo Gatti, Ionut Constantinescu, Catholijn Jonker, Kyriaki Kalimeri, Pradeep Kumar Murukannaiah
| Challenge: | Existing methods to analyze whether a text classifier learns the domain-specific expression of moral language are lacking. |
| Approach: | They propose a method to compare a supervised classifier’s representation of moral rhetoric across domains by exploring similarities and differences between moral concepts and domains. |
| Outcome: | The proposed method compares a supervised classifier’s representation of moral rhetoric across domains and domains. |
An Information-Providing Closed-Domain Human-Agent Interaction Corpus (L18-1)
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| Challenge: | a human-agent interaction corpus is a corpus of conversations between a user and an embodied conversational agent operated by a wizard of oz . data collected to create a 'corpus' with unexpected situations, such as misunderstandings, false information, and interruptions. |
| Approach: | They propose a public corpus for Human-Agent Interaction where the agent is controlled by a Wizard of Oz. |
| Outcome: | The proposed corpus is based on 15 conversations between users and a wizard of Oz agent . the data are used to create a corpus with unexpected situations, such as misunderstandings, false information, and interruptions. |