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1. A Transparency Paradox? Investigating the Impact of Explanation Specificity and Autonomous Vehicle Perceptual Inaccuracies on Passengers

2. S-RAF: A Simulation-Based Robustness Assessment Framework for Responsible Autonomous Driving

3. Learning Run-time Safety Monitors for Machine Learning Components

4. RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language Model

5. CC-SGG: Corner Case Scenario Generation using Learned Scene Graphs

6. Effects of Explanation Specificity on Passengers in Autonomous Driving

7. Textual Explanations for Automated Commentary Driving

8. Explainable Action Prediction through Self-Supervision on Scene Graphs

9. From Spoken Thoughts to Automated Driving Commentary: Predicting and Explaining Intelligent Vehicles' Actions

10. A Fait Accompli? An Empirical Study into the Absence of Consent to Third-Party Tracking in Android Apps

11. Explanations in Autonomous Driving: A Survey

12. A Step Towards Exposing Bias in Trained Deep Convolutional Neural Network Models

13. Smooth Grad-CAM++: An Enhanced Inference Level Visualization Technique for Deep Convolutional Neural Network Models

14. Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa

15. EEG-based Communication with a Predictive Text Algorithm

16. Deep Convolutional Neural Network for Plant Seedlings Classification

17. Web Security Investigation through Penetration Tests: A Case study of an Educational Institution Portal

18. Realizing the Potential of AI in Africa: It All Turns on Trust

28. Towards Explainable and Trustworthy Autonomous Physical Systems

29. Why Not Explain? Effects of Explanations on Human Perceptions of Autonomous Driving

30. Fairness and Transparency in Human-Robot Interaction.

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