Papers with Pairwise Evaluation
PEAR: Pairwise Evaluation for Automatic Relative Scoring in Machine Translation (2026.acl-long)
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| Challenge: | PEAR is a supervised quality estimation metric that reframes reference-free machine translation evaluation as a graded pairwise comparison. |
| Approach: | They propose to use a supervised quality estimation metric family to reframe machine translation evaluation as a graded pairwise comparison. |
| Outcome: | The proposed metric outperforms strictly matched single-candidate QE baselines on the WMT24 meta-evaluation benchmark. |