Hannah Erlebach
DPhil in Machine Learning @ FLAIR, University of Oxford
About
I’m in the first year of my PhD in machine learning supervised by Jakob Foerster. I'm grateful to receive funding from the Cooperative AI PhD fellowship.
I did my masters in machine learning at University College London, and undergraduate in maths at Cambridge.
Research
My previous research has focused on cooperation in language models and multi-agent reinforcement learning settings.
- DUA: Discovering Universal Attacks Using Foundation Models. Master's thesis for UCL MSc in Machine Learning, 2025.
- Guiding Evolution of Artificial Life Using Vision-Language Models. Nikhil Baid, Hannah Erlebach, Paul Hellegouarch and Frederico Wieser. Published in Artificial Life Conference 2025. [arXiv]
- Mitigating Goal Misgeneralisation via Minimax Regret. Karim Abdel Sadek, Matthew Farrugia-Roberts, Usman Anwar, Hannah Erlebach, Christian Schroeder de Witt, David Krueger and Michael Dennis. Published in Reinforcement Learning Conference 2025. [arXiv]
- RACCOON: Regret-based Adaptive Curricula for Cooperation. Hannah Erlebach and Jonathan Cook. Published in CoCoMARL workshop at Reinforcement Learning Conference 2024.
- Welfare Diplomacy: Benchmarking Language Model Cooperation. Gabriel Mukobi, Hannah Erlebach, Niklas Lauffer, Lewis Hammond, Alan Chan and Jesse Clifton. Published in SoLaR workshop at NeurIPS 2023. [arXiv]