Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge (2022.acl-long)
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| Challenge: | Existing methods to improve machine reading comprehension (MRC) tasks require unstated knowledge to perform well. |
| Approach: | They propose to extract a new kind of structured knowledge from scripts and use it to improve machine reading comprehension (MRC) They propose a teacher-student paradigm to facilitate the transfer of knowledge in weakly-labeled MRC data. |
| Outcome: | The proposed method outperforms methods that use weakly-labeled data and improves a state-of-the-art baseline by 4.3% in accuracy on a Chinese multiple-choice MRC dataset C3. |
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