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Related Questions
- How do different training objectives, such as masked language modeling and next sentence prediction, impact the ability of language models to generate coherent text?
- What role does the size and complexity of the training dataset play in determining the contextual relevance of generated text?
- Can you explain the relationship between the training objectives and the ability of language models to capture nuances of language, such as idioms and figurative language?
- How do training objectives influence the ability of language models to generate text that is consistent with the input context?
- What is the impact of training objectives on the ability of language models to recognize and generate text that is relevant to a specific domain or topic?
- Can you discuss the trade-offs between different training objectives, such as maximizing coherence versus maximizing contextual relevance?
- How do training objectives affect the ability of language models to generalize to new, unseen text and maintain their performance over time?
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