English(EN) Efficient One-to-Many Translation with Joint Multi-Stream Diffusion

扩散模型实现高效的一对多机器翻译

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-16 04:00

研究人员开发了一种新颖的基于扩散的一对多机器翻译框架，显著提高了效率和灵活性。该方法并行优化所有目标语言，实现了与语言数量成亚线性延迟扩展，并使单个模型能够取代多个独立的翻译系统。该框架在未见过的语言上表现出强大的零样本迁移能力，无需重新训练，质量约为监督翻译的75%。通过加速采样，与传统的自回归基线相比，它提供了2倍的速度提升和改进的零样本BLEU分数。 AI

影响这种基于扩散的方法可以显著加速和简化AI系统的多语言翻译任务。

排序理由详细介绍一种新机器翻译方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Yiwen Guan, Jacob Whitehill · 2026-09-16 04:00

使用联合多流扩散进行高效的一对多翻译

arXiv:2609.16312v1 Announce Type: cross Abstract: One-to-many machine translation (MT) is computationally expensive for autoregressive (AR) systems, which suffer from linear latency scaling with both sequence length and the number of target languages. We explore how diffusion can…

本文如何被排名

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使用联合多流扩散进行高效的一对多翻译

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