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Related Questions
- How does paraphrasing with varying levels of abstraction or granularity affect the performance of language models in different domains?
- Can language models generalize better when trained on paraphrased data with different levels of abstraction or granularity?
- What are the implications of using paraphrased data with varying levels of abstraction or granularity on the generalizability of language models to new tasks or domains?
- How does the level of abstraction or granularity in paraphrased data impact the ability of language models to capture semantic relationships and nuances?
- Can language models learn to adapt to different levels of abstraction or granularity in paraphrased data, and if so, how?
- What are the potential trade-offs between using paraphrased data with high abstraction or granularity versus low abstraction or granularity in terms of generalizability?
- How can the level of abstraction or granularity in paraphrased data be optimized for improving the generalizability of language models?
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