Papers with word embeddings models
Towards Qualitative Word Embeddings Evaluation: Measuring Neighbors Variation (N18-4)
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| Challenge: | Using extrinsic evaluation methods, embeddings are evaluated on a specific task such as part-of-speech tagging or named-entity recognition. |
| Approach: | They propose a method to study the variation between word embeddings models trained with only one parameter by observing the distributional neighbors variation. |
| Outcome: | The proposed method shows that changing only one parameter can have a massive impact on a given semantic space. |
Igbo Diacritic Restoration using Embedding Models (N18-4)
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| Challenge: | Igbo is a low-resource language spoken by approximately 30 million people worldwide. |
| Approach: | They propose to use word embeddings to restore diacritics in Igbo by using a pre-processing task that replaces missing diacrittics on words from which they have been removed. |
| Outcome: | The embedding models performed better than n-gram models on the diacritic restoration task. |
Few-Shot Learning Translation from New Languages (2025.emnlp-main)
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| Challenge: | Recent work shows strong transfer learning capability to unseen languages in sequence-to-sequence neural networks . current transfer learning methods require much less downstream task data than would otherwise be required. |
| Approach: | They first train word embeddings models on varying amounts of data and plug them into a machine translation model. |
| Outcome: | The proposed model can learn Flores with only 500 parallel sentences and 31,250 sentences of monolingual data, and it can exceed 15 BLEU on unseen languages. |
Facilitating Corpus Usage: Making Icelandic Corpora More Accessible for Researchers and Language Users (2020.lrec-1)
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| Challenge: | Gigaword corpus is a large text corpus used in natural language processing . large corpora are needed to achieve better performance in the field of NLP . |
| Approach: | They propose a set of tools to facilitate the use of the Icelandic Gigaword Corpus . they provide n-grams based on the corpus, and a variety of pre-trained word embeddings models . |
| Outcome: | The proposed tools facilitate the use of the Icelandic Gigaword corpus in the field of Natural Language Processing and other fields. |