Papers with WikiCQA dataset
Closed-book Question Generation via Contrastive Learning (2023.eacl-main)
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| Challenge: | Recent studies on open-book QG have achieved promising progress, but generating natural questions under a more practical closed-book setting remains a challenge. |
| Approach: | They propose a QG model that stores more information in its parameters through contrastive learning and an answer reconstruction module. |
| Outcome: | The proposed model outperforms baselines in automatic evaluation and human evaluation on a public dataset and a new WikiCQA dataset. |