On guaranteed optimal robust explanations for NLP models
We build on abduction-based explanations for machine learning and develop a method for computing local explanations for neural network models in natural language processing (NLP). Our explanations comprise a subset of the words of the input text that satisfies two key features: optimality w.r.t. a u...
| 主要な著者: | , , , , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
International Joint Conferences on Artificial Intelligence
2021
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