Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning

Run more RL experiments. Wait less for GPUs.

[CVPR 2026] Official Code for "ARM-Thinker: Reinforcing Multimodal Generative Reward Models with Agentic Tool Use and Visual Reasoning"

Claw-R1: Empowering OpenClaw with Advanced Agentic RL.

[ACL 2026 Findings] Thinking with Map: Reinforced Parallel Map-Augmented Agent for Geolocalization

DART-GUI: Efficient Multi-turn RL for GUI Agents via Decoupled Training and Adaptive Data Curation

Curated, opinionated index of post-R1 LLM × Reinforcement Learning. Many deep-dive blog posts cross-linked to many papers — GRPO, DAPO, DPO, PPO, RLHF, GSPO, CISPO, VAPO, Reward Modeling, MoE RL stability, Verifier-Free RL, Training-Free RL, Agentic RL, DeepSeek-R1 reproduction.

Proximity-based Multi-turn Optimization (ProxMO) - Official Implementation

SGLang model provider for Strands Agents for on-policy agentic RL training.

[ACL2026] AlphaQuanter: An End-to-End Tool-Orchestrated Agentic Reinforcement Learning Framework for Stock Trading.

Standardizing environment infrastructure with Strands Agents — step, observe, reward.

This is the official repository for our paper "Doctor-R1: Mastering Clinical Inquiry with Experiential Agentic Reinforcement Learning" published in ICRL 2026.

Official implementation for paper "Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents: A Comprehensive Recipe"

Official Code of Paper: MolAct: An Agentic RL Framework for Molecular Editing and Property Optimization

Train and customize OpenClaw agents using reinforcement learning with simple language feedback and fully asynchronous optimization.