4 papers · 1 filter
The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
Xu Wan, Speed Zhu, Jianwei Cai +4
Inference-time scaling has emerged as a critical avenue for enhancing Large Language Models' performance, yet real-world deployment is constrained by strict computational budgets.…
Buffer Matters: Unleashing the Power of Off-Policy Reinforcement Learning in Large Language Model Reasoning
Xu Wan, Yansheng Wang, Wenqi Huang +1
Traditional on-policy Reinforcement Learning with Verifiable Rewards (RLVR) frameworks suffer from experience waste and reward homogeneity, which directly hinders learning efficien…
Think Twice, Act Once: A Co-Evolution Framework of LLM and RL for Large-Scale Decision Making
Xu Wan, Wenyue Xu, Chao Yang +1
Recent advancements in Large Language Models (LLMs) and Reinforcement Learning (RL) have shown significant promise in decision-making tasks. Nevertheless, for large-scale industria…
SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning
Xu Wan, Chao Yang, Cheng Yang +2
Although multi-agent reinforcement learning (MARL) has shown its success across diverse domains, extending its application to large-scale real-world systems still faces significant…