4 papers · 1 filter
Enhancing VLM Reward Models Through Structure-Aware Fine-Tuning
Pyrros Koussios, Chenhao Li, Xin Chen +1
Designing effective reward functions remains a major bottleneck in Reinforcement Learning (RL). Recent work uses large foundation Vision-Language Models (VLMs) as reward models, co…
Model-Based Reinforcement Learning for Control under Time-Varying Dynamics
Klemens Iten, Bruce Lee, Chenhao Li +3
Learning-based control methods typically assume stationary system dynamics, an assumption often violated in real-world systems due to drift, wear, or changing operating conditions.…
Symmetry-Guided Memory Augmentation for Efficient Locomotion Learning
Kaixi Bao, Chenhao Li, Yarden As +2
Training reinforcement learning (RL) policies for legged locomotion often requires extensive environment interactions, which are costly and time-consuming. We propose Symmetry-Guid…
Feature-Based vs. GAN-Based Learning from Demonstrations: When and Why
Chenhao Li, Marco Hutter, Andreas Krause
This survey provides a comparative analysis of feature-based and GAN-based approaches to learning from demonstrations, with a focus on the structure of reward functions and their i…