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Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention
In this paper, we present a novel approach for the task of eXplainable Question Answering (XQA), i. e., generating natural language (NL) explanations for the Visual Question Answering (VQA) problem.
A Study on Multimodal and Interactive Explanations for Visual Question Answering
Explainability and interpretability of AI models is an essential factor affecting the safety of AI.
Explainable Artificial Intelligence (XAI)
Question Answering
+1
Learning Invariant World State Representations with Predictive Coding
Herein, we propose a framework for evaluating visual representations for illumination invariance in the context of depth perception.
Improving the Robustness of Quantized Deep Neural Networks to White-Box Attacks using Stochastic Quantization and Information-Theoretic Ensemble Training
We present a method to improve the robustness of quantized DNNs to white-box adversarial attacks.
