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ICLR 2026 Agentic Reinforced Policy Optimization (ARPO)
Implementation for ACL'25 paper TreeRL: LLM Reinforcement Learning with On-Policy Tree Search. The implementation is based on OpenRLHF
This is the official implementation of TreePO algorithm.
```bash conda create -n rllm python=3.10 -y conda activate rllm
β¨ Getting Started β’ π Introduction π§ Usage β’ π Evaluation β’ π Citation β’ π» Acknowledgement β’ π Star History
The main features of prime-rl/prime are: Critic-Based Algorithms, Dense Reward Optimization, Policy Optimization.
Projects with overlapping indexed features include: thudm/treerl β Implementation for ACL'25 paper TreeRL: LLM Reinforcement Learning with On-Policy Tree Search. The implementation isβ¦ yangzhch6/treerpo β ```bash conda create -n rllm python=3.10 -y conda activate rllm. multimodal-art-projection/treepo β This is the official implementation of TreePO algorithm. ruc-nlpir/arpo β [ICLR 2026] Agentic Reinforced Policy Optimization (ARPO). trademaster-ntu/trademaster β TradeMaster is a reinforcement learning trading framework and algorithmic trading simulator designed for designing andβ¦ chenxinan-fdu/polaris β π A PO st-training recipe for scaling R L on A dvanced R eason I ng model S π.