Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates (2022.emnlp-main)
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| Challenge: | Existing methods to improve confidence calibration of pre-trained language models are still a mystery. |
| Approach: | They propose a method that leverages model explanations to make models less confident with non-inductive attributions. |
| Outcome: | The proposed method improves confidence calibration in all settings and reduces calibration errors when combined with temperature scaling. |
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