Web: http://arxiv.org/abs/2206.07690

June 20, 2022, 1:11 a.m. | Vikram V. Ramaswamy, Sunnie S. Y. Kim, Nicole Meister, Ruth Fong, Olga Russakovsky

cs.LG updates on arXiv.org arxiv.org

Deep learning models have achieved remarkable success in different areas of
machine learning over the past decade; however, the size and complexity of
these models make them difficult to understand. In an effort to make them more
interpretable, several recent works focus on explaining parts of a deep neural
network through human-interpretable, semantic attributes. However, it may be
impossible to completely explain complex models using only semantic attributes.
In this work, we propose to augment these attributes with a small …

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