Learning Altruistic Behaviours in Reinforcement Learning without External Rewards. - Tim Franzmeyer; Mateusz Malinowski; João F. Henriques (ICLR, 2022)

Learn what matters: cross-domain imitation learning with task-relevant embeddings. - Tim Franzmeyer; Philip H. S. Torr; João F. Henriques (NeurIPS, 2022)

Illusionary Attacks on Sequential Decision Makers and Countermeasures. - Tim Franzmeyer; João F. Henriques; Jakob N. Foerster; Philip H. S. Torr; Adel Bibi; Christian Schröder de Witt (CoRR, 2022)

Scalable Biologically-Aware Skeleton Generation for Connectomic Volumes. - Brian Matejek; Tim Franzmeyer; Donglai Wei 001; Xueying Wang 002; Jinglin Zhao; Kálmán Palágyi; Jeff W. Lichtman; Hanspeter Pfister (IEEE Trans. Medical Imaging, 2022)

Extracting Reward Functions from Diffusion Models. - Felipe Nuti; Tim Franzmeyer; João F. Henriques (NeurIPS, 2023)

HelloFresh: LLM Evalutions on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits. - Tim Franzmeyer; Aleksandar Shtedritski; Samuel Albanie; Philip Torr 001; João F. Henriques; Jakob N. Foerster (ACL (Findings), 2024)

Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection. - Linas Nasvytis; Kai Sandbrink; Jakob N. Foerster; Tim Franzmeyer; Christian Schröder de Witt (AAMAS, 2024)

Select to Perfect: Imitating desired behavior from large multi-agent data. - Tim Franzmeyer; Edith Elkind; Philip Torr 001; Jakob Nicolaus Foerster; João F. Henriques (ICLR, 2024)

Illusory Attacks: Information-theoretic detectability matters in adversarial attacks. - Tim Franzmeyer; Stephen Marcus McAleer; João F. Henriques; Jakob Nicolaus Foerster; Philip Torr 001; Adel Bibi; Christian Schröder de Witt (ICLR, 2024)

HelloFresh: LLM Evaluations on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits. - Tim Franzmeyer; Aleksandar Shtedritski; Samuel Albanie; Philip Torr 001; João F. Henriques; Jakob N. Foerster (CoRR, 2024)

Select2Plan: Training-Free ICL-Based Planning through VQA and Memory Retrieval. - Davide Buoso; Luke Robinson; Giuseppe Averta; Philip Torr 001; Tim Franzmeyer; Daniele De Martini (CoRR, 2024)

High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning. - Tim Franzmeyer; Archie Sravankumar; Lijuan Liu; Yuning Mao; Rui Hou; Sinong Wang; Jakob N. Foerster; Luke Zettlemoyer; Madian Khabsa (CoRR, 2025)

TuCo: Measuring the Contribution of Fine-Tuning to Individual Responses of LLMs. - Felipe Nuti; Tim Franzmeyer; João F. Henriques (CoRR, 2025)