Papers with unsupervised paraphrase generation
MCPG: A Flexible Multi-Level Controllable Framework for Unsupervised Paraphrase Generation (2022.findings-emnlp)
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| Challenge: | Existing studies on controllable unsupervised paraphrase generation are expensive and require supervised training on large parallel corpora. |
| Approach: | They propose a method for controllable unsupervised paraphrase generation that is flexible to adapt to specific domains without extra training. |
| Outcome: | The proposed method outperforms state-of-the-art unsupervised baselines by a margin. |
Generating Sentences from Disentangled Syntactic and Semantic Spaces (P19-1)
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| Challenge: | Variational auto-encoders (VAEs) are widely used in natural language generation due to the regularization of the latent space. |
| Approach: | They propose to generate sentences from disentangled syntactic and semantic spaces by using the linearized tree sequence. |
| Outcome: | The proposed method achieves similar or better performance in various tasks compared with state-of-the-art models. |
Gradient-guided Unsupervised Lexically Constrained Text Generation (2020.emnlp-main)
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| Challenge: | Existing methods for lexically constrained generation fail when the search space is too large . a novel method to solve the problem is based on gradient-guided optimization . |
| Approach: | They propose a method to solve lexically-constrained generation as an unsupervised gradient-guided optimization problem. |
| Outcome: | The proposed method achieves state-of-the-art compared to previous methods . it is free of parallel data training, flexible to be used in the inference stage of any pre-trained generation model. |