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Related Questions
- What are the key differences in evaluation metrics used in extrinsic and intrinsic evaluation of language models?
- How do extrinsic evaluation methods assess the performance of language models in real-world tasks, whereas intrinsic evaluation focuses on internal properties?
- Can you provide examples of evaluation criteria used in extrinsic evaluation, such as BLEU score or ROUGE score, and how they differ from intrinsic metrics like perplexity or entropy?
- How do extrinsic evaluation methods account for the context and nuances of real-world tasks, whereas intrinsic evaluation is more focused on the model's internal workings?
- What are the limitations of intrinsic evaluation in predicting a model's performance on real-world tasks, and how do extrinsic evaluation methods address these limitations?
- Can you explain the relationship between extrinsic and intrinsic evaluation, and how they complement each other in the evaluation of language models?
- How do extrinsic evaluation methods, such as human evaluation or task-based evaluation, compare to intrinsic evaluation in terms of objectivity and reliability?
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