Based on these findings, we share the higher-level layers 2 between the entailment generation and sentence simplification tasks, since they share higher semantic-level language inference skills (for full sentence-to-sentence logical directedness).
(2017) observed that different layers in a sequence-tosequence model (trained on translation) exhibit different functionalities: lower-layers (closer to inputs) of the encoder learn to represent word structure while higher layers (farther from inputs) are more focused on semantics and meanings (Zeiler and Fergus (2014) observed similar findings for convolutional image features).