Papers by Woo Tae Jeong
Generating Diverse and Consistent QA pairs from Contexts with Information-Maximizing Hierarchical Conditional VAEs (2020.acl-main)
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| Challenge: | Existing models for question answering are limited in the availability of labeled data. |
| Approach: | They propose a hierarchical conditional variational autoencoder for generating QA pairs given unstructured texts as contexts while maximizing mutual information between generated QA pair to ensure consistency. |
| Outcome: | The proposed framework achieves impressive performance gains over baseline models on both tasks, using only a fraction of data for training. |