Near-Future Policy Optimization
From Daily Paper Cast by Jingwen Liang, Gengyu Wang
April 24, 2026 · 22 min · Episode 1799
About this episode
The episode discusses Near-Future Policy Optimization in reinforcement learning, focusing on improving convergence and performance through mixed-policy methods.
🤗 Upvotes: 45 | cs.LG Authors: Chuanyu Qin, Chenxu Yang, Qingyi Si, Naibin Gu, Dingyu Yao, Zheng Lin, Peng Fu, Nan Duan, Jiaqi Wang Title: Near-Future Policy Optimization Arxiv: http://arxiv.org/abs/2604.20733v1 Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a core post-training recipe. Introducing suitable off-policy trajectories into on-policy exploration accelerates RLVR convergence and raises the performance ceiling, yet finding a source of such trajectories remains the key challenge. Existing mixed-policy methods either import trajectories from external teachers (high-quality but distributionally far) or replay past training trajectories (close but capped in quality), and neither simultaneously satisfies the strong enough (higher $Q$ , more new knowledge to learn) and close enough (lower $V$ , more readily absorbed) conditions required to maximize the effective learning signal $\mathcal{S} = Q/V$. We propose \textbf{N}ear-Future \textbf{P}olicy \textbf{O}ptimization (\textbf{NPO}), a simple mixed-policy scheme that learns from a policy's own near-future self: a later checkpoint from the same training run is a natural source of auxiliary…
People in this episode
Hosts: Jingwen Liang, Gengyu Wang
Topics covered
- Reinforcement Learning
- Policy Optimization
- Machine Learning
- Artificial Intelligence
- Trajectory Learning
Keywords
- Reinforcement Learning
- Policy Optimization
- Mixed-Policy
- Trajectory
- AutoNPO
Mentioned in this episode
Books & works: Near-Future Policy Optimization
More episodes of Daily Paper Cast
- EvoArena: Tracking Memory Evolution for Robust LLM Agents in Dynamic Environments · June 13, 2026 · 24 min
- MiniMax Sparse Attention · June 13, 2026 · 26 min
- SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning · June 13, 2026 · 23 min
- InterleaveThinker: Reinforcing Agentic Interleaved Generation · June 13, 2026 · 21 min
- FORT-Searcher: Synthesizing Shortcut-Resistant Search Tasks for Training Deep Search Agents · June 13, 2026 · 23 min
- Robust-U1: Can MLLMs Self-Recover Corrupted Visual Content for Robust Understanding? · June 13, 2026 · 20 min
Explore listener stats, chart rankings, contacts and more on the Daily Paper Cast podcast page.