Style Over Substance: Evaluation Biases for Large Language Models (2025.coling-main)
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| Challenge: | Ranking the relative performance of large language models based on Elo ratings is gaining popularity . however, the extent to which humans and LLMs are capable evaluators remains uncertain . |
| Approach: | They propose to evaluate machine-generated text across multiple dimensions using the Elo rating system . they propose to use crowd-sourced and expert annotators to rank models based on Elo ratings . |
| Outcome: | The proposed method improves the quality of LLM-based evaluations, but there is no improvement in crowd-sourced evaluations. |
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