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Related Questions
- How can suboptimal tokenization impact the understanding and contextualization of a prompt in a large language model?
- Can suboptimal tokenization cause semantic loss or degradation of contextual relationships between words within a text input?
- In what ways might suboptimal tokenization contribute to biases in large language model output or underutilization of model capacities?
- What approaches exist to re-tokenization to correct or minimize adverse impacts on performance, in a given instance of text-to-text language models and more widely.
- Do some architectures perform consistently more poorly or show stronger tolerance under such issues regarding its structure versus traditional types or newer BERT transformer configurations
- Beyond affecting downstream processing performance: would an improper splitting reduce understanding on subcomponent-wise interpretation?
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