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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.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…