Papers by Matteo Guida
MFTCXplain: A Multilingual Benchmark Dataset for Evaluating the Moral Reasoning of LLMs through Multi-hop Hate Speech Explanation (2025.findings-emnlp)
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Jackson Trager, Francielle Vargas, Diego Alves, Matteo Guida, Mikel K. Ngueajio, Ameeta Agrawal, Yalda Daryani, Farzan Karimi Malekabadi, Flor Miriam Plaza-del-Arco
| Challenge: | Existing evaluation benchmarks for large language models lack annotations that justify moral classifications and focus on English constrain moral reasoning across diverse cultural settings. |
| Approach: | They propose a multilingual benchmark dataset for evaluating moral reasoning of large language models . it includes 3,000 tweets annotated with binary hate speech labels, moral categories and rationales . |
| Outcome: | The proposed dataset shows a misalignment between LLM outputs and human annotations in moral reasoning tasks. |
Self-Explaining Hate Speech Detection with Moral Rationales (2026.findings-acl)
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Francielle Vargas, Jackson Trager, Diego Alves, Matteo Guida, Surendrabikram Thapa, Berk Atıl, Daryna Dementieva, Andrew J Smart, Ameeta Agrawal
| Challenge: | Existing models for hate speech detection are opaque and rely on surface-level cues. Existing approaches often encode biases originating from training data and annotation processes. |
| Approach: | They propose a framework that integrates moral rationale supervision into training . they propose SMRA for self-explaining hate speech detection . |
| Outcome: | The proposed framework improves performance across binary hate speech detection and multi-label moral sentiment classification. |
Not all ANIMALs are equal: metaphorical framing through source domains and semantic frames (2026.findings-acl)
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| Challenge: | a computational framework allows to derive discourse metaphors through their source domains and semantic frames. |
| Approach: | They propose a computational framework that allows to derive salient discourse metaphors through their source domains and semantic frames. |
| Outcome: | The proposed framework uncovers well-known source domains and reveals nuanced frame-level associations that distinguish how the issue is portrayed. |
Article and Comment Frames Shape the Quality of Online Comments (2026.findings-acl)
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| Challenge: | Recent work has focused on predicting comment toxicity or quality, but it ignores audience reactions. |
| Approach: | They propose a frame-aware system to mitigate unhealthy discourse . they analysed 1M comments across 2.7K news articles . |
| Outcome: | The proposed system can mitigate unhealthy discourses by analyzing 1M comments across 2.7K news articles. |