Neural Natural Language Inference Models Enhanced with External Knowledge
Table 3: Accuracies of models on MultiNLI. * indicates models using extra SNLI training set.
['[BOLD] Model', '[BOLD] In', '[BOLD] Cross']
The baseline ESIM achieves 76.8% and 75.8% on in-domain and cross-domain test set, respectively. If we extend the ESIM with external knowledge, we achieve significant gains to 77.2% and 76.4% respectively. Again, the gains are consistent on SNLI and MultiNLI, and we expect they would be orthogonal to other factors when external knowledge is added into other state-of-the-art models.