Calibrating Model-Based Evaluation Metrics for Summarization (2026.findings-acl)
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| Challenge: | Recent advances in summary evaluation are based on model-based metrics to assess quality dimensions, such as completeness, conciseness, and faithfulness. |
| Approach: | They propose a general framework that generates individual and average proxy scores without relying on reference summaries, human annotations, or expensive model-based metrics. |
| Outcome: | The proposed framework outperforms baselines on seven datasets on continuous-value scenarios, such as summarization, but is applicable to discrete-value tasks, such QA. |
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