Unsupervised Text Generation byLearning from Search
Table 2: Automatic evaluation results on formality transfer. ↓The smaller, the better.
['Methods', 'iBLEU', 'BLEU']
Among the unsupervised approaches, the simulated annealing model UPSA Liu et al. sampling Bowman et al. We propose to use large-scale pretrained language models for fluency and evaluation (mode name: SA w/ PLM), and improve iBLEU by 2.5 points from UPSA. Our tgls framework of search and learning further improves iBLEU by 2.96 points, being a new state-of-the-art unsupervised paraphrasing model. Again, we see consistent evidence on the effectiveness of tgls, as it outperforms existing unsupervised approaches including heuristic marking of style words and retrieval-based editing Li et al.