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Related Questions
- What are the key differences between automatic metrics and human evaluation metrics in assessing the quality of LLM-generated summaries?
- Can you explain the potential limitations of relying solely on automatic metrics for evaluating LLM-generated summaries?
- How do automatic metrics, such as ROUGE and BLEU, calculate the similarity between generated summaries and reference summaries?
- What are some common challenges associated with using automatic metrics for evaluating the coherence and fluency of LLM-generated summaries?
- How can human evaluation metrics, such as human judgment and crowdsourcing, provide a more comprehensive understanding of the quality of LLM-generated summaries?
- What are some potential biases in automatic metrics that can affect the evaluation of LLM-generated summaries?
- Can you discuss the importance of using a combination of automatic and human evaluation metrics for a more accurate assessment of LLM-generated summaries?
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