Papers by Víctor Suárez-Paniagua
Combining Denoising Autoencoders with Contrastive Learning to fine-tune Transformer Models (2023.emnlp-main)
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| Challenge: | Recent advances in NLP have led to the use of pre-trained Transformer models for transfer learning tasks becoming the most common way to solve target tasks. |
| Approach: | They propose a 3-phase technique to adjust a base model for a classification task by adapting the model’s signal to the data distribution and a new data augmentation approach for Supervised Contrastive Learning to correct the unbalanced datasets. |
| Outcome: | The proposed method is compared with other methods and compares it with other approaches. |
VSP at PharmaCoNER 2019: Recognition of Pharmacological Substances, Compounds and Proteins with Recurrent Neural Networks in Spanish Clinical Cases (D19-57)
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| Challenge: | The Named Entity Recognition of drugs, medications and chemical entities in Spanish is a new task in the field of NLP . |
| Approach: | They propose to use SNOMED CT term search engine to classify the entities in Spanish and a neural model for the Named Entity Recognition. |
| Outcome: | The proposed system achieves 76.29% and 60.34% performance in the Named Entity Recognition and Concept indexing tasks. |