Papers with human ratings
RankME: Reliable Human Ratings for Natural Language Generation (N18-2)
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| Challenge: | Existing studies have shown that human evaluation for natural language generation often suffers from inconsistent user ratings. |
| Approach: | They propose a rank-based magnitude estimation method which combines continuous scales and relative assessments to improve the reliability of human ratings. |
| Outcome: | The proposed method significantly improves the reliability and consistency of human ratings compared to traditional evaluation methods. |
A Dual-Perspective NLG Meta-Evaluation Framework with Automatic Benchmark and Better Interpretability (2025.acl-long)
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| Challenge: | Existing evaluation metrics are insufficient to meet requirements for natural language generation. |
| Approach: | They propose a dual-perspective NLG meta-evaluation framework that focuses on different evaluation capabilities and a method of automatically constructing benchmarks without requiring new human annotations. |
| Outcome: | The proposed framework improves interpretability and provides better performance for 16 representative LLMs. |