Papers by Damian Sastre
Predicting Embedding Reliability in Low-Resource Settings Using Corpus Similarity Measures (2022.lrec-1)
Copied to clipboard
| Challenge: | a paper aims to evaluate embedding similarity, stability and reliability in low-resource settings . it uses corpus similarity measures before training to predict properties of embeddables . |
| Approach: | They use corpus similarity measures before training to predict properties of embeddings . they then apply the same measures to low-resource settings by modelling reliability . authors hope to use this method to evaluate low-source languages with limited corpus size . |
| Outcome: | The paper shows that it is possible to predict downstream embedding similarity using upstream corpus similarity measures . the main finding is that the measures remain robust on small amounts of training data . |