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Coverage Guided Testing for Recurrent Neural Networks
[article]
2020
arXiv
pre-print
Recurrent neural networks (RNNs) have been applied to a broad range of applications such as natural language processing, drug discovery, and video recognition. This paper develops a coverage-guided testing approach for a major class of RNNs -- long short-term memory networks (LSTMs). We start from defining a family of three test metrics that are designed to quantify not only the values but also the temporal relations (including both step-wise and bounded-length) learned through LSTM's internal
arXiv:1911.01952v2
fatcat:hm6emtrxs5bbraa7qs7jn66idy