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Related Questions
- How do graph-based neural networks handle long-range dependencies in language data?
- Can graph-based neural networks better capture the complex relationships between entities in natural language?
- Do graph-based neural networks have any benefits in terms of handling out-of-vocabulary words in language modeling?
- How do graph-based neural networks compare to traditional architectures in terms of parallelization and training efficiency?
- Are there any applications of graph-based neural networks in specific NLP tasks such as text classification or named entity recognition?
- How do graph-based neural networks handle noise and sparsity in the input data compared to traditional architectures?
- Can graph-based neural networks be used for multi-task learning and domain adaptation in language modeling?
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