Papers by Boxuan Lyu

1 papers
Unveiling the Power of Source: Source-based Minimum Bayes Risk Decoding for Neural Machine Translation (2025.acl-long)

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Challenge: Maximum a posteriori decoding aims to maximize the estimated posterior probability, but high estimated probability does not always lead to high translation quality.
Approach: They propose a method that seeks hypotheses with the highest expected utility by using quasi-sources as “support hypothese . they propose sMBR decoding which utilizes a reference-free quality estimation metric as the utility function.
Outcome: The proposed approach outperforms QE reranking and the standard MBR decoding.

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