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Related Questions
- How can back-translation be used to enhance language model performance by exploiting the symmetry of translation?
- What is the role of paraphrasing in improving language model accuracy, and how can it be combined with word dropout and text manipulation?
- Can you explain how text manipulation techniques such as tokenization and contextualized embeddings can be used to improve language model understanding of nuanced language?
- How can masked language modeling, a variation of word dropout, be used to improve language model performance on out-of-distribution data?
- What is the advantage of using a combination of back-translation and data augmentation techniques to improve language model robustness?
- Can you demonstrate how text manipulation techniques, such as replacing named entities with placeholders, can help improve language model performance in tasks like question answering?
- How can multilingual language models, combined with back-translation, be used to improve the performance of a language model on a target language dataset?
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