Papers with MixQG
MixQG: Neural Question Generation with Mixed Answer Types (2022.findings-naacl)
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| Challenge: | Existing neural question generation approaches focus on short factoid type of answers. |
| Approach: | They propose a neural question generator that trains a single generative model by combining multiple question types with different answer types. |
| Outcome: | The proposed model outperforms existing models in both seen and unseen domains and can generate questions with different cognitive levels when conditioned on different answer types. |