Papers with DeepLIFT

1 papers
Evaluating neural network explanation methods using hybrid documents and morphosyntactic agreement (P18-1)

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Challenge: a number of post hoc explanation methods for deep neural networks have been proposed . due to the complexity of the DNNs they explain, these methods are necessarily approximations and come with their own sources of error.
Approach: They propose two evaluation paradigms that cover two important classes of NLP problems . they propose LIMSSE, LRP and DeepLIFT as the most effective explanation methods .
Outcome: The proposed methods are most effective for explaining deep neural networks in NLP . the proposed methods can explain complex models without manual annotation .

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