| An assurance case pattern for the interpretability of machine learning in safety-critical systems FR Ward, I Habli Computer Safety, Reliability, and Security. SAFECOMP 2020 Workshops: DECSoS …, 2020 | 19 | 2020 |
| Geometric deep learning for post-menstrual age prediction based on the neonatal white matter cortical surface V Vosylius, A Wang, C Waters, A Zakharov, F Ward, L Le Folgoc, J Cupitt, ... Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2020 | 15 | 2020 |
| Honesty is the best policy: defining and mitigating AI deception F Ward, F Toni, F Belardinelli, T Everitt Advances in Neural Information Processing Systems 36, 2024 | 9 | 2024 |
| On Agent Incentives to Manipulate Human Feedback in Multi-Agent Reward Learning Scenarios. FR Ward, F Toni, F Belardinelli AAMAS, 1759-1761, 2022 | 4 | 2022 |
| The reasons that agents act: Intention and instrumental goals FR Ward, M MacDermott, F Belardinelli, F Toni, T Everitt arXiv preprint arXiv:2402.07221, 2024 | 2 | 2024 |
| Defining deception in structural causal games FR Ward, F Toni, F Belardinelli Proceedings of the 2023 International Conference on Autonomous Agents and …, 2023 | 2 | 2023 |
| Towards Defining Deception in Structural Causal Games FR Ward NeurIPS ML Safety Workshop, 2022 | 2 | 2022 |
| Tall tales at different scales: Evaluating scaling trends for deception in language models FR Ward, F Hofstätter, LA Thomson, HM Wood, O Jaffe, P Bartak, ... | 1 | 2023 |
| Argumentative reward learning: Reasoning about human preferences FR Ward, F Belardinelli, F Toni arXiv preprint arXiv:2209.14010, 2022 | 1 | 2022 |
| A Causal Perspective on AI Deception in Games. FR Ward, F Toni, F Belardinelli AISafety@ IJCAI, 2022 | 1 | 2022 |
| Experiments with Detecting and Mitigating AI Deception I Sahbane, FR Ward, CH Åslund arXiv preprint arXiv:2306.14816, 2023 | | 2023 |
Ibrahim HabliProfessor of Safety-Critical Systems at the University of YorkVerified email at york.ac.uk
