Papers by Adam Storek

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Challenge:	Unsupervised selective rationalization produces rationales alongside predictions, but does not ensure that the rationale contains a plausible explanation for the prediction.
Approach:	They propose a technique that injects noise between a rationale generator and a predictor to limit generation of implausible rationales.
Outcome:	The proposed method achieves significant improvements in plausibility and task accuracy over the state-of-the-art models while maintaining or improving model faithfulness.