Encode, Tag, Realize: High-Precision Text Editing
Table 2: Sentence fusion results on DfWiki.
['Model', 'Exact', 'SARI']
Comparison against Baselines. We obtain new SOTA results with LaserTaggerAR, outperforming the previous SOTA 7-layer Transformer model from geva2019discofuse by 2.7% Exact score and 1.0% SARI score. We also find that the pretrained seq2seqBERT model yields nearly as good performance, demonstrating the effectiveness of unsupervised pretraining for generation tasks. The performance of the tagger is impaired significantly when leaving out the SWAP tag due to the model’s inability to reconstruct 10.5% of the training set.