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Paper develops a new unsupervised scoring function for cross-lingual document alignment.

problem Aligning documents across different languages for NLP tasks.
method Uses cross-lingual sentence embeddings to compute semantic distances and guides document alignment.
result The proposed scoring function outperforms current methods by 7-22% on various language pairs.

Recurrent Neural Networks (RNNs) have been proven to be effective in modeling sequential data and they have been applied to boost a variety of tasks such as document classification, speech recognition and machine translation. Most of existing RNN models have been designed for sequences assumed to be identically and ind…

2018-08-19abs ↗pdf ↗

In many real-world problems, we are dealing with collections of high-dimensional data, such as images, videos, text and web documents, DNA microarray data, and more. Often, high-dimensional data lie close to low-dimensional structures corresponding to several classes or categories the data belongs to. In this paper, we…

2012-03-05abs ↗pdf ↗