Papers by Kieran Heese
Integrated Directional Gradients: Feature Interaction Attribution for Neural NLP Models (2021.acl-long)
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| Challenge: | Existing methods for attribution of importance to features borrowed from cooperative game theory . success of Deep Neural Networks has led to their ability to learn from complex higher order interactions from raw features. |
| Approach: | They propose a method for attributing importance scores to groups of features . they propose axioms that any intuitive feature group attribution method should satisfy . |
| Outcome: | The proposed method captures the importance of features in a linguistic model using negations and conjunctions. |