4 papers
A Systematic Investigation of RL-Jailbreaking in LLMs
Montaser Mohammedalamen, Kevin Roice, Reginald McLean +1
The evolution of generative models from next-token predictors to autonomous engines of complex systems necessitates rigorous safety hardening. Adversarial jailbreaking, the strateg…
Meta-World+: An Improved, Standardized, RL Benchmark
Reginald McLean, Evangelos Chatzaroulas, Luc McCutcheon +9
Meta-World is widely used for evaluating multi-task and meta-reinforcement learning agents, which are challenged to master diverse skills simultaneously. Since its introduction how…
Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics
Minttu Alakuijala, Reginald McLean, Isaac Woungang +4
Natural language is often the easiest and most convenient modality for humans to specify tasks for robots. However, learning to ground language to behavior typically requires impra…
Multi-Task Reinforcement Learning Enables Parameter Scaling
Reginald McLean, Evangelos Chatzaroulas, Jordan Terry +3
Multi-task reinforcement learning (MTRL) aims to endow a single agent with the ability to perform well on multiple tasks. Recent works have focused on developing novel sophisticate…