Papers by David Hurych
LLM as a Meta-Judge: Synthetic Data for NLP Evaluation Metric Validation (2026.acl-srw)
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| Challenge: | Existing evaluation metrics for natural language generation are expensive and time-consuming. |
| Approach: | They propose a framework that utilizes LLMs to generate synthetic evaluation datasets . they propose meta-correlation to measure alignment between metric rankings and human benchmarks based on synthetic data . |
| Outcome: | The proposed framework achieves meta-correlations exceeding 0.9 in multilingual QA and replaces human judgment with synthetic evaluation datasets. |