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

An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.

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