Papers with machine translation reranking

1 papers
Early-Exit and Instant Confidence Translation Quality Estimation (2026.eacl-long)

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Challenge: Quality estimation models are often opaque and computationally expensive, making them impractical to be part of large-scale pipelines.
Approach: They propose an uncertainty-aware quality estimation model that matches previous approaches at a fraction of their costs.
Outcome: The proposed method reduces evaluation costs by 50% and improves reranking performance.

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