3 papers
cs.LG2026
LLMs Can Learn to Reason Via Off-Policy RL
Daniel Ritter, Owen Oertell, Bradley Guo +3
Reinforcement learning (RL) approaches for Large Language Models (LLMs) frequently use on-policy algorithms, such as PPO or GRPO. However, policy lag from distributed training arch…
cs.RO2025
High-Altitude Balloon Station-Keeping with First Order Model Predictive Control
Myles Pasetsky, Jiawei Lin, Bradley Guo +1
High-altitude balloons (HABs) are common in scientific research due to their wide range of applications and low cost. Because of their nonlinear, underactuated dynamics and the par…
cs.LG2025
Scaling Offline RL via Efficient and Expressive Shortcut Models
Nicolas Espinosa-Dice, Yiyi Zhang, Yiding Chen +5
Diffusion and flow models have emerged as powerful generative approaches capable of modeling diverse and multimodal behavior. However, applying these models to offline reinforcemen…