Abstract
We present a toolkit to facilitate the interpretation and understanding of neural network models. The toolkit provides several methods to identify salient neurons with respect to the model itself or an external task. A user can visualize selected neurons, ablate them to measure their effect on the model accuracy, and manipulate them to control the behavior of the model at the test time. Such an analysis has a potential to serve as a springboard in various research directions, such as understanding the model, better architectural choices, model distillation and controlling data biases. The toolkit is available for download.
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CITATION STYLE
Dalvi, F., Nortonsmith, A., Bau, A., Belinkov, Y., Sajjad, H., Durrani, N., & Glass, J. (2019). Neurox: A toolkit for analyzing individual neurons in neural networks. In 33rd AAAI Conference on Artificial Intelligence, AAAI 2019, 31st Innovative Applications of Artificial Intelligence Conference, IAAI 2019 and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019 (pp. 9851–9852). AAAI Press. https://doi.org/10.1609/aaai.v33i01.33019851
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