Multi-Task Dense Retrieval via Model Uncertainty Fusion for Open-Domain Question Answering (2021.findings-emnlp)
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| Challenge: | Existing approaches to multitask dense retrieval are not effective due to corpus inconsistency. |
| Approach: | They propose to train individual dense passage retrievers for different open-domain question-answering tasks and aggregate their predictions during test time. |
| Outcome: | The proposed method achieves state-of-the-art performance on 5 benchmark QA datasets, with up to 10% improvement in top-100 accuracy compared to a joint-training multi-task DPR on SQuAD. |
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