Learning to request guidance in emergent language. - Benjamin Kolb; Leon Lang; Henning Bartsch; Arwin Gansekoele; Raymond Koopmanschap; Leonardo Romor; David Speck 002; Mathijs Mul; Elia Bruni (LANTERN@EMNLP-IJCNLP, 2019)

Learning to Request Guidance in Emergent Communication. - Benjamin Kolb; Leon Lang; Henning Bartsch; Arwin Gansekoele; Raymond Koopmanschap; Leonardo Romor; David Speck 002; Mathijs Mul; Elia Bruni (CoRR, 2019)

A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels. - Leon Lang; Maurice Weiler (ICLR, 2021)

A Program to Build E(N)-Equivariant Steerable CNNs. - Gabriele Cesa; Leon Lang; Maurice Weiler (ICLR, 2022)

Information Decomposition Diagrams Applied beyond Shannon Entropy: A Generalization of Hu's Theorem. - Leon Lang; Pierre Baudot; Rick Quax; Patrick Forré (CoRR, 2022)

Evaluating Shutdown Avoidance of Language Models in Textual Scenarios. - Teun van der Weij; Simon Lermen; Leon Lang (CoRR, 2023)

When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback. - Leon Lang; Davis Foote; Stuart J. Russell; Anca D. Dragan; Erik Jenner; Scott Emmons (NeurIPS, 2024)

When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning. - Leon Lang; Davis Foote; Stuart Russell 001; Anca D. Dragan; Erik Jenner; Scott Emmons (CoRR, 2024)

The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret. - Lukas Fluri; Leon Lang; Alessandro Abate; Patrick Forré; David Krueger 001; Joar Skalse (CoRR, 2024)

Abstract Markov Random Fields. - Leon Lang; Clélia de Mulatier; Rick Quax; Patrick Forré (CoRR, 2024)

Factored space models: Towards causality between levels of abstraction. - Scott Garrabrant; Matthias Georg Mayer; Magdalena Wache; Leon Lang; Sam Eisenstat; Holger Dell (CoRR, 2024)

Modeling Human Beliefs about AI Behavior for Scalable Oversight. - Leon Lang; Patrick Forré (CoRR, 2025)