Simulating Bandit Learning from User Feedback for Extractive Question Answering (2022.acl-long)
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| Challenge: | Explicit feedback from users can be used to continually improve system performance. |
| Approach: | They study the potential of learning from user feedback for extractive question answering by simulating feedback using supervised data. |
| Outcome: | The proposed model improves on a few examples and can be deployed in new domains without any data annotation effort. |
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