Papers with unsupervised neural acceptability model
Unsupervised Parsing via Constituency Tests (2020.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for unsupervised parsing rely on constituency tests . linguists can judge a sentence's grammatical validity by modifying it via some transformation . |
| Approach: | They propose a method for unsupervised parsing based on a constituency test . they specify a set of transformations and use an unsupervised neural acceptability model to make grammaticality decisions. |
| Outcome: | The proposed method achieves 62.8 F1 on the Penn Treebank test set, an improvement of 7.6 points over the previous best results. |