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Related Questions
- Can self-supervised learning techniques, such as masked language modeling, improve the ability of LLMs to generate novel metaphors?
- In what ways do language models leverage self-supervised learning to enhance their metaphorical understanding and generation capabilities?
- How do the training objectives of self-supervised learning influence the creative and original output of metaphor generation in LLMs?
- What role does the concept of 'latent spaces' play in self-supervised learning for LLMs, and how does it impact metaphor generation?
- Can self-supervised learning help LLMs to learn abstract concepts, such as metaphors, in a more nuanced and context-dependent manner?
- How do self-supervised learning techniques, such as language modeling, affect the ability of LLMs to capture and generate subtle metaphorical relationships?
- What are the potential limitations of using self-supervised learning for metaphor generation in LLMs, and how can they be addressed?
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