← authors · overview

• Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning
  2021 · 35 citations
• Policy Regularization via Noisy Advantage Values for Cooperative Multi-agent Actor-Critic methods
  2021 · 8 citations
• QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning
  2020 · 7 citations
• REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization
  2025 · 2 citations
• OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
  2024 · 1 citations
• Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning
  2026
• Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training
  2025
• ProRL Agent: Rollout-as-a-Service for RL Training of Multi-Turn LLM Agents
  2026
• Golden Goose: A Simple Trick to Synthesize Unlimited RLVR Tasks from Unverifiable Internet Text
  2026
• BroRL: Scaling Reinforcement Learning via Broadened Exploration
  2025
• Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving
  2025
• ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
  2025