Enhancing Sentence Embedding with Generalized Pooling
Table 2: Accuracies of the models on the MultiNLI dataset.
['[BOLD] Model', '[BOLD] In', '[BOLD] Cross']
The first group is the results of previous sentence-encoding-based models. The proposed model with generalized pooling achieves an accuracy of 73.8% on the in-domain test set and 74.0% on the cross-domain test set; both improve over the baselines using max pooling, mean pooling and last pooling. In addition, the results on cross-domain test set yield a new state of the art at an accuracy of 74.0%, which is better than 73.6% of shortcut-stacked BiLSTM