On Modifying a Neural Network's Perception
- URL: http://arxiv.org/abs/2303.02655v1
- Date: Sun, 5 Mar 2023 12:09:37 GMT
- Title: On Modifying a Neural Network's Perception
- Authors: Manuel de Sousa Ribeiro and Jo\~ao Leite
- Abstract summary: We propose a method which allows one to modify what an artificial neural network is perceiving regarding specific human-defined concepts.
We test the proposed method on different models, assessing whether the performed manipulations are well interpreted by the models, and analyzing how they react to them.
- Score: 3.42658286826597
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Artificial neural networks have proven to be extremely useful models that
have allowed for multiple recent breakthroughs in the field of Artificial
Intelligence and many others. However, they are typically regarded as black
boxes, given how difficult it is for humans to interpret how these models reach
their results. In this work, we propose a method which allows one to modify
what an artificial neural network is perceiving regarding specific
human-defined concepts, enabling the generation of hypothetical scenarios that
could help understand and even debug the neural network model. Through
empirical evaluation, in a synthetic dataset and in the ImageNet dataset, we
test the proposed method on different models, assessing whether the performed
manipulations are well interpreted by the models, and analyzing how they react
to them.
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