most citedBenefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective

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cs.AI2026

RL-VLA: A Flexible and Asynchronous Reinforcement Learning Framework for VLA Training

Haoran Sun, Yongjian Guo, Zhong Guan +13

Reinforcement learning (RL) has emerged as a critical paradigm for post-training Vision-Language-Action (VLA) models, enabling embodied agents to adapt and improve through environm…

cs.AI2026★ 1 cited

Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective

Siwei Wang, Yifei Shen, Haoran Sun +5

Recent reinforcement learning (RL) methods have substantially enhanced the planning capabilities of Large Language Models (LLMs), yet the theoretical basis for their effectiveness…