Towards Transparent AI Systems: Interpreting Visual Question Answering Models

Understand

Deep neural networks have shown striking progress and obtained state-of-the-art results in many AI research fields in the recent years.

• However, it is often unsatisfying to not know why they predict what they do.
• In this paper, we address the problem of interpreting Visual Question Answering (VQA) models.
• Specifically, we are interested in finding what part of the input (pixels in images or words in questions) the VQA model focuses on while answering the question.