8 citations · 24 across the 6 of their papers we have counts for
4 papers · 1 filter
Uncovering Layer-Dependent Activation Sparsity Patterns in ReLU Transformers
Cody Wild, Jesper Anderson
Previous work has demonstrated that MLPs within ReLU Transformers exhibit high levels of sparsity, with many of their activations equal to zero for any given token. We build on tha…
An Empirical Investigation of Representation Learning for Imitation
Xin Chen, Sam Toyer, Cody Wild +9
Imitation learning often needs a large demonstration set in order to handle the full range of situations that an agent might find itself in during deployment. However, collecting e…
The MineRL BASALT Competition on Learning from Human Feedback
Rohin Shah, Cody Wild, Steven H. Wang +10
The last decade has seen a significant increase of interest in deep learning research, with many public successes that have demonstrated its potential. As such, these systems are n…
Adversarial Policies: Attacking Deep Reinforcement Learning
Adam Gleave, Michael Dennis, Cody Wild +3
Deep reinforcement learning (RL) policies are known to be vulnerable to adversarial perturbations to their observations, similar to adversarial examples for classifiers. However, a…