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Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features.
Interpretable neural predictions with differentiable binary variables
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Thien Huu Nguyen and Ralph Grishman. 2015 · 2015
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Rationalizing neural predictions
Tao Lei, Regina Barzilay, and Tommi Jaakkola. 2016 · 2016
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Aspect-augmented adversarial networks for domain adaptation
Yuan Zhang, Regina Barzilay, and Tommi Jaakkola. 2017 · 2017
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Mingmin Zhao, Shichao Yue, Dina Katabi, Tommi S Jaakkola, and Matt T Bianchi. 2017 · 2017
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Extractive adversarial networks: High-recall explanations for identifying personal attacks in social media posts
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Game-theoretic interpretability for temporal modeling
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Neural module networks
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Learning to explain: An information-theoretic perspective on model interpretation
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Learning corresponded rationales for text matching
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