Papers by José Cañete
Evaluation Benchmarks for Spanish Sentence Representations (2022.lrec-1)
Copied to clipboard
Vladimir Araujo, Andrés Carvallo, Souvik Kundu, José Cañete, Marcelo Mendoza, Robert E. Mercer, Felipe Bravo-Marquez, Marie-Francine Moens, Alvaro Soto
| Challenge: | Existing and newly constructed datasets address different tasks from various domains. |
| Approach: | They propose to use Spanish SentEval and Spanish DiscoEval to evaluate stand-alone and discourse-aware sentence representations. |
| Outcome: | The proposed benchmarks evaluate the capabilities of stand-alone and discourse-aware sentence representations in Spanish and show that they are more robust and comparable than previous benchmarks. |
Speedy Gonzales: A Collection of Fast Task-Specific Models for Spanish (2024.starsem-1)
Copied to clipboard
| Challenge: | Large language models (LLMs) are a common and successful approach to language and retrieval tasks. |
| Approach: | They evaluate the available large language models in Spanish and then use knowledge distillation to refine and distill them. |
| Outcome: | The proposed models are fine-tuned and distilled on knowledge distillation and are available on huggingface.co/dccuchile. |
ALBETO and DistilBETO: Lightweight Spanish Language Models (2022.lrec-1)
Copied to clipboard
| Challenge: | Recent advances in pre-trained language models have made them more popular . however, there are still limited versions of these models for other languages . |
| Approach: | They present ALBETO and DistilBETO which are versions of ALBERT and DistillBERT pre-trained exclusively on Spanish corpora. |
| Outcome: | The proposed models outperform BETO and ALBERT on Spanish datasets . the models outpace BETO on MLDoc, PAWS-X, XNLI, MLQA, SQAC and XQuAD datasets. |