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New model enhances bilingual lexicon induction with latent variables

作者 PulseAugur 编辑部 · [1 个来源] ·

This paper introduces a new discriminative latent variable model designed for bilingual lexicon induction. The model integrates a bipartite matching dictionary prior with a representation-based approach. Researchers developed an efficient Viterbi EM algorithm for training and demonstrated improved bilingual lexicons across six language pairs and two metrics, also showing how prior work can be viewed through a similar latent-variable model lens. AI

排序理由 The item is an academic paper published on arXiv detailing a new model for bilingual lexicon induction. [lever_c_demoted from research: ic=1 ai=1.0]

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New model enhances bilingual lexicon induction with latent variables

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The item is an academic paper published on arXiv detailing a new model for bilingual lexicon induction. [lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Sebastian Ruder, Ryan Cotterell, Yova Kementchedjhieva, Anders S{\o}gaard ·

    一种用于双语词汇归纳的判别式潜在变量模型

    arXiv:1808.09334v4 Announce Type: replace-cross Abstract: We introduce a novel discriminative latent variable model for bilingual lexicon induction. Our model combines the bipartite matching dictionary prior of Haghighi et al. (2008) with a representation-based approach (Artetxe …

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