Programming to Learn: Logic and Computation from a Programming Perspective. - Matthew Farrugia-Roberts; Bryn Jeffries; Harald Søndergaard (ITiCSE (1), 2022)

Teaching Simple Constructive Proofs with Haskell Programs. - Matthew Farrugia-Roberts; Bryn Jeffries; Harald Søndergaard (TFPIE, 2022)

Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. - Joar Max Viktor Skalse; Matthew Farrugia-Roberts; Stuart Russell 001; Alessandro Abate; Adam Gleave (ICML, 2023)

Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks. - Matthew Farrugia-Roberts (NeurIPS, 2023)

Computational Complexity of Detecting Proximity to Losslessly Compressible Neural Network Parameters. - Matthew Farrugia-Roberts (CoRR, 2023)

The Developmental Landscape of In-Context Learning. - Jesse Hoogland; George Wang; Matthew Farrugia-Roberts; Liam Carroll; Susan Wei; Daniel Murfet (CoRR, 2024)

Loss Landscape Degeneracy and Stagewise Development in Transformers. - Jesse Hoogland; George Wang; Matthew Farrugia-Roberts; Liam Carroll; Susan Wei; Daniel Murfet (Trans. Mach. Learn. Res., 2025)

Dynamics of Transient Structure in In-Context Linear Regression Transformers. - Liam Carroll; Jesse Hoogland; Matthew Farrugia-Roberts; Daniel Murfet (CoRR, 2025)

You Are What You Eat - AI Alignment Requires Understanding How Data Shapes Structure and Generalisation. - Simon Pepin Lehalleur; Jesse Hoogland; Matthew Farrugia-Roberts; Susan Wei; Alexander Gietelink Oldenziel; George Wang; Liam Carroll; Daniel Murfet (CoRR, 2025)

Mitigating Goal Misgeneralization via Minimax Regret. - Karim Abdel Sadek; Matthew Farrugia-Roberts; Usman Anwar; Hannah Erlebach; Christian A. Schröder de Witt; David Krueger 001; Michael Dennis 001 (CoRR, 2025)