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Related Questions
- How do the fixed-length input limitations of BERT and RoBERTa affect their ability to capture long-range dependencies in natural language processing tasks?
- Can the fixed-length input limitations of BERT and RoBERTa be overcome through the use of techniques such as document-level processing or multi-sentence input?
- What are the implications of the fixed-length input limitations of BERT and RoBERTa for tasks that require modeling long-range dependencies, such as question answering or text classification?
- How do the fixed-length input limitations of BERT and RoBERTa compare to those of other language models, such as Transformer-XL or Longformer?
- Can the fixed-length input limitations of BERT and RoBERTa be mitigated through the use of techniques such as attention mechanisms or memory-augmented networks?
- What are the potential applications of BERT and RoBERTa in tasks that require modeling long-range dependencies, despite their fixed-length input limitations?
- How do the fixed-length input limitations of BERT and RoBERTa impact their performance on tasks that require modeling long-range dependencies in different languages or domains?
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