Sequence Decoding Methods
Discriminative Adversarial Search
Introduced by Scialom et al. in Discriminative Adversarial Search for Abstractive SummarizationDiscriminative Adversarial Search, or DAS, is a sequence decoding approach which aims to alleviate the effects of exposure bias and to optimize on the data distribution itself rather than for external metrics. Inspired by generative adversarial networks (GANs), wherein a discriminator is used to improve the generator, DAS differs from GANs in that the generator parameters are not updated at training time and the discriminator is only used to drive sequence generation at inference time.
Source: Discriminative Adversarial Search for Abstractive Summarization
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Autonomous Driving | 1 | 20.00% |
| Reinforcement Learning (RL) | 1 | 20.00% |
| Self-Learning | 1 | 20.00% |
| Abstractive Text Summarization | 1 | 20.00% |
| Domain Adaptation | 1 | 20.00% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
