Author

Shengji Tang

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#artificial intelligence May 2026

StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction

StraTA is a simple framework that introduces an explicit trajectory-level strategy into agentic reinforcement learning (RL) and trains strategy generation and action execution jointly with a hierarchical GRPO-style rollout design, further enhanced by diverse strategy rollout and critical self-judgment.

Xiangyuan Xue, Yifan Zhou, Zidong Wang et al. · arXiv.org · 1 citation

Review Aug 2026

SimpleOPD: Simple Tokenizer-Agnostic On-Policy Distillation for Long-Context Reasoning

This work introduces a student reference KL loss and mask the advantages of special termination tokens to mitigate the problem of excessive generation length and frequent truncation, and improves on science benchmarks such as HLE and HiPhO, suggesting that OPD transfers reasoning capabilities that generalize beyond the...

Haonan He, Hao Lei, Yun Luo et al. · 3 citations · ⚡1