Papers by Pedro Ferreira
Explanation Regularisation through the Lens of Attributions (2025.coling-main)
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| Challenge: | Explanation regularisation (ER) is a method to guide text classifiers to form their predictions relying on tokens that humans consider plausible. |
| Approach: | They introduce an auxiliary explanation loss to measure how well an input attribution technique's output agrees with human-annotated rationales. |
| Outcome: | The proposed model improves classification performance in out-of-domain (OOD) settings by relying on tokens humans consider plausible. |
AIA-BDE: A Corpus of FAQs in Portuguese and their Variations (2020.lrec-1)
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Hugo Gonçalo Oliveira, João Ferreira, José Santos, Pedro Fialho, Ricardo Rodrigues, Luisa Coheur, Ana Alves
| Challenge: | a corpus of 380 domain-oriented FAQs in Portuguese is presented . paraphrases or entailed questions are created manually, by humans, or automatically, with Google Translate. |
| Approach: | They present a corpus of 380 domain-oriented FAQs in Portuguese and their variations, i.e., paraphrases or entailed questions, created manually, by humans, or automatically, with Google Translate. |
| Outcome: | The proposed system outperforms other systems in the domain of question-answering . it performs well when matching variations with their original questions . |
Sparse and Constrained Attention for Neural Machine Translation (P18-2)
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| Challenge: | Existing approaches to address coverage problem only change attention transformations . adequacy of neural machine translation is still a major concern . |
| Approach: | They propose a new approach that allocates fertilities to source words to bound attention . they propose gating architectures and adaptive attention control to control the amount of source context . |
| Outcome: | The proposed model is differentiable and sparse and is evaluated in three languages pairs. |