Methods › Natural Language Processing › Sequence Decoding Methods › Discriminative Adversarial Search
Discriminative Adversarial Search
Introduced by Thomas Scialom et al. in Discriminative Adversarial Search for Abstractive Summarization
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Discriminative 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.
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms 29 Oct 2022 · 2 repositories · arXiv:2210.16575
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Discriminative Adversarial Search for Abstractive Summarization 24 Feb 2020 · 1 repository · arXiv:2002.10375
Tasks archive 2025-07-28
8 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Abstractive Text Summarization | 1 |
| Autonomous Driving | 1 |
| Diversity | 1 |
| Domain Adaptation | 1 |
| Reinforcement Learning (RL) | 1 |
| Safe Reinforcement Learning | 1 |
| Self-Learning | 1 |
| Transfer Learning | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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