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Related Questions
- How does a fixed-size contextualization window impact a model's ability to learn from long-range dependencies?
- Can a fixed-size window limit a model's capacity to adapt to rapidly changing language styles or dialects?
- What are some potential solutions to address the limitations of fixed-size contextualization windows in language models?
- How does the size of the contextualization window affect a model's ability to capture nuances in language?
- Are there any trade-offs between the size of the contextualization window and the model's computational efficiency?
- Can a fixed-size window lead to overfitting or underfitting in language models?
- How can the choice of contextualization window size be optimized for specific language tasks or domains?
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