37 citations · 38 across the 5 of their papers we have counts for
6 papers
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning
Zhao Yang, Yuxuan Jiang, Ting-Chih Chen +18
Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a narrow slice of what RL offers.…
Reinforcement Learning from Cross-domain Videos with Video Prediction Model
Zhao Yang, Xinrui Zu, Jacob E. Kooi +5
Reinforcement learning from expert videos across visually distinct domains is challenging due to the absence of reward signals and the presence of domain gaps. We introduce XIPER (…
Hadamax Encoding: Elevating Performance in Model-Free Atari
Jacob E. Kooi, Zhao Yang, Vincent François-Lavet
Neural network architectures have a large impact in machine learning. In reinforcement learning, network architectures have remained notably simple, as changes often lead to small…
Hadamard Representation: Scaffolding Performance Across Model-free RL
Jacob E. Kooi, Zhao Yang, Mark Hoogendoorn +1
Deep reinforcement learning agents progressively lose representational capacity during training: neurons become dormant, removing active capacity from the network, and effective ra…
Disentangled (Un)Controllable Features
Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
In the context of MDPs with high-dimensional states, downstream tasks are predominantly applied on a compressed, low-dimensional representation of the original input space. A varie…
Inclined Quadrotor Landing using Deep Reinforcement Learning
Jacob E. Kooi, Robert Babuška
Landing a quadrotor on an inclined surface is a challenging maneuver. The final state of any inclined landing trajectory is not an equilibrium, which precludes the use of most conv…