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Related Questions
- What are some common evaluation metrics used to measure the coherence of text generated by language models?
- How can we quantify the relevance of text generated by language models to a given context or prompt?
- What are some potential biases in evaluating the performance of text generation models, and how can we mitigate them?
- Can you discuss the role of human evaluators in assessing the performance of text generation models, and how can we ensure their judgments are reliable and consistent?
- What are some challenges in evaluating the performance of text generation models in low-resource languages or domains?
- How can we evaluate the ability of text generation models to generate text that is both coherent and diverse?
- What are some best practices for using automated evaluation metrics to evaluate the performance of text generation models, and when to use human evaluation instead?
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