Papers by Francesco Giannini

1 papers
Extending Logic Explained Networks to Text Classification (2022.emnlp-main)

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Challenge: Recent studies have proposed explainable-by-design neural models providing logic explanations for their predictions, but these models favour global explanations, while local ones tend to be noisy and verbose.
Approach: They propose to use LENp to improve local explanations by perturbing input words to improve sensitivity and faithfulness of local explanation.
Outcome: The proposed model provides better local explanations than LIME and is more user-friendly than Lime as attested by a human survey.

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