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English(EN) TACTICS: Taxonomy-Aware Intelligent Corpus Sampling for Machine Translation

新的TACTICS方法增强了机器翻译评估

研究人员开发了TACTICS,一种用于智能语料库采样的创新方法,旨在改进机器翻译系统的评估。该方法通过从地区风格指南中诱导分层分类法并据此对片段进行分类,将覆盖率重塑为明确的目标。TACTICS选择一个固定预算的子集,以优化稀有类别、文档级连贯性和对完整语料库的分布保真度。在机器翻译评估中应用TACTICS,已证明其在稀有类别覆盖方面优于传统的基于词汇和基于嵌入的选择方法。 AI

排序理由 该集群包含一篇详细介绍机器翻译评估新方法的 ist 研究论文。

在 arXiv cs.CL 阅读 →

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新的TACTICS方法增强了机器翻译评估

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该集群包含一篇详细介绍机器翻译评估新方法的 ist 研究论文。
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Prasanth Bathala, Anubhav Shrimal, Sukhdeep Singh Kharbhanda, Pradyumna Lanka, Rohit Dhaipule ·

    TACTICS:面向机器翻译的感知智能语料库采样策略

    arXiv:2609.17956v1 Announce Type: new Abstract: Large-scale machine-translation (MT) systems are typically evaluated on random samples from a corpus whose distributional composition is an artifact of how it was assembled. Such a sample inherits the phenomena the collection happen…