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Hey there, fellow researchers! When diving into perplexity scores, what exciting factors should we keep in mind for accurate interpretation? Let's explore the nuances together! From model performance to dataset characteristics, there's so much to uncover. What insights can we gather to enhance our understanding of these intriguing metrics?

What should researchers consider when interpreting perplexity scores?

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