Papers by Helena Caseli
Choosing What to Mask: More Informed Masking for Multimodal Machine Translation (2023.acl-srw)
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| Challenge: | Pre-trained language models have achieved remarkable results on several NLP tasks. |
| Approach: | They propose three new masking strategies for cross-lingual visual pre-training that focus on learning different linguistic patterns. |
| Outcome: | The proposed methods outperform the baseline model and achieve state-of-the-art accuracy on the Portuguese-English MMT task. |
Identifying Fine-grained Depression Signs in Social Media Posts (2024.lrec-main)
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| Challenge: | Currently, most studies focus on a binary classification setup or on pre-established resources. |
| Approach: | They evaluated machine learning techniques to model 21 depression signs in social media posts from Brazilian undergraduate students. |
| Outcome: | The proposed methods struggle to classify the majority of depression signs on social media posts, compared with the majority on the social media sites. |
NMT and PBSMT Error Analyses in English to Brazilian Portuguese Automatic Translations (2020.lrec-1)
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| Challenge: | Recent work proposes neural machine translation (NMT) for Brazilian Portuguese. |
| Approach: | They propose a neural machine translation approach that generates equivalent sentences in target language and source language. |
| Outcome: | The proposed approach outperforms phrase-based statistical machine translation systems for some pairs of languages. |
Multilingual and Multimodal Learning for Brazilian Portuguese (2022.lrec-1)
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| Challenge: | Existing models that learn multimodal and multilingual representations perform better in many natural language tasks. |
| Approach: | They use a multimodal and multilingual corpus to test its generalization ability for other languages . they achieve a BLEU score of 51.8 and a METEOR score of 78.0 on the test set . |
| Outcome: | The proposed model outperforms the existing model on a Portuguese-English multimodal translation task. |