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Related Questions
- What is the relationship between the size of the pre-training dataset and the model's capacity to capture contextual nuances in language?
- How does the quality and quantity of the pre-training data affect the ability of BERT and RoBERTa to disambiguate word senses?
- Can large pre-training datasets help mitigate the issue of polysemy and homography in language understanding?
- How does the size of the pre-training dataset influence the model's ability to recognize idiomatic expressions and figurative language?
- What are the implications of using smaller vs. larger pre-training datasets on the performance of BERT and RoBERTa in downstream tasks?
- How does the pre-training dataset size impact the model's ability to learn semantic relationships between words and their context?
- Can the use of larger pre-training datasets help improve the model's ability to generalize to out-of-domain texts and tasks?
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