Papers with supervised QA models
Handling Anomalies of Synthetic Questions in Unsupervised Question Answering (2020.coling-main)
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| Challenge: | Existing approaches to improve unsupervised Question Answering (UQA) are expensive and require additional datasets. |
| Approach: | They propose an unsupervised QA approach that generates QA training data automatically. |
| Outcome: | The proposed method improves unsupervised QA significantly across a number of QA tasks. |
An Empirical Comparison of LM-based Question and Answer Generation Methods (2023.findings-acl)
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| Challenge: | Question and answer generation (QAG) is a task of generating question-answer pairs given a context. |
| Approach: | They propose to leverage sequence-to-sequence language model fine-tuning to generate question-answer pairs given a context. |
| Outcome: | The proposed model outperforms other more convoluted approaches in the end-to-end model and is computationally light at both training and inference times. |