A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators (C18-1)
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| Challenge: | Existing research on visual question generation is focused on training models to fit the annotated data set that makes them indifferent from other language generation tasks. |
| Approach: | They propose to use two discriminators to enhance the training of a visual question generator to ask natural questions about an image. |
| Outcome: | The proposed model outperforms state-of-the-art models in terms of automatic and human evaluation metrics. |
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