Learning Paraphrastic Sentence Embeddingsfrom Back-Translated Bitext
Table 12: Diversity filtering test results after tuning filtering hyperparameters on development data (averaged over languages and data sources for the NMT rows). Results are on STS datasets (Pearson’s r×100).
['Filtering Method', 'NMT GRAN', 'NMT Avg', 'SimpWiki GRAN', 'SimpWiki Avg']
We find that the diversity filtering methods lead to consistent improvements when training on SimpWiki. We believe this is because many of the sentence pairs in SimpWiki are near-duplicates and these filtering methods favor data with more differences.