LLMs as Narcissistic Evaluators: When Ego Inflates Evaluation Scores (2024.findings-acl)
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| Challenge: | Existing evaluation metrics for natural language generation tasks favor text generated by different LMs . human evaluation by experts is the most reliable approach, but it is costly and time-consuming . |
| Approach: | They examine whether language model-driven evaluation metrics exhibit bias toward underlying language models in the context of summarization tasks. |
| Outcome: | The proposed evaluation metrics tend to assign inflated scores to outputs generated by the very model they are based on. |
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