Papers by ZiXian Huang
When Retriever-Reader Meets Scenario-Based Multiple-Choice Questions (2021.findings-emnlp)
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| Challenge: | Scenario-based question answering (SQA) requires retrieving and reading paragraphs from a large corpus to answer a question contextualized by a long scenario description. |
| Approach: | They propose a model where the retriever is implicitly supervised only using QA labels via a novel word weighting mechanism. |
| Outcome: | The proposed model outperforms strong baselines on multiple-choice questions in three datasets. |