Papers with analysis of neural sequence-to-sequence models

1 papers
A Detailed Evaluation of Neural Sequence-to-Sequence Models for In-domain and Cross-domain Text Simplification (L18-1)

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Challenge: Xu et al., 2016) show that a simple neural architecture can be efficiently used for in-domain and cross-domain text simplification.
Approach: They evaluate neural sequence-to-sequence models for text simplification on Wikipedia and Newsela datasets.
Outcome: The proposed model can generalize across corpora and overcome challenges when tested on Wikipedia and Newsela datasets.

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