3 papers
cs.DC2026
Polar: Agentic RL on Any Harness at Scale
Binfeng Xu, Hao Zhang, Shaokun Zhang +9
Reinforcement learning for language agents increasingly depends on custom harnesses that manage long-running context, multi-turn tool use and multi-agent orchestration. However, po…
cs.LG2026
Empowering Multi-Turn Tool-Integrated Agentic Reasoning with Group Turn Policy Optimization
Yifeng Ding, Hung Le, Songyang Han +5
Training Large Language Models (LLMs) for multi-turn Tool-Integrated Reasoning (TIR) - where models iteratively reason, generate code, and verify through execution - remains challe…
cs.AI2026
ProRL Agent: Rollout-as-a-Service for RL Training of Multi-Turn LLM Agents
Hao Zhang, Mingjie Liu, Shaokun Zhang +10
Multi-turn LLM agents are increasingly important for solving complex, interactive tasks, and reinforcement learning (RL) is a key ingredient for improving their long-horizon behavi…