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Related Questions
- How can suboptimal tokenization impact the performance of transformer-based models in NLP tasks?
- What are some common causes of suboptimal tokenization in text data, and how can they be addressed?
- What are the differences between rule-based and learned tokenization approaches, and which one is more effective in alleviating the effects of suboptimal tokenization?
- Can you explain how suboptimal tokenization can lead to biased or unfair model outputs, and how can this be mitigated?
- What role does tokenization play in the overall pipeline of NLP tasks, and how can it impact the effectiveness of downstream tasks?
- How can active learning techniques be used to identify and correct suboptimal tokenization in large datasets?
- What are some strategies for evaluating the effectiveness of tokenization approaches in mitigating the effects of suboptimal tokenization?
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