Papers with gradient propagation process
Adversarial Text Generation via Sequence Contrast Discrimination (2020.findings-emnlp)
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| Challenge: | Existing approaches to generate human-like texts are auto-regressive, but they suffer from exposure bias due to the dependence on the previous sampled output during the inferring phase. |
| Approach: | They propose a sequence contrast loss driven text generation framework which learns the difference between real texts and generated texts and uses that difference. |
| Outcome: | The proposed framework improves training stability and quality of generated texts and avoids the time-consuming sampling process. |