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Auditing and Robustifying COVID-19 Misinformation Datasets via Anticontent Sampling
This paper makes two key contributions.
Practical Benefits of Feature Feedback Under Distribution Shift
In attempts to develop sample-efficient and interpretable algorithms, researcher have explored myriad mechanisms for collecting and exploiting feature feedback (or rationales) auxiliary annotations provided for training (but not test) instances that highlight salient evidence.
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