GitHub

verl: Volcano Engine Reinforcement Learning for LLMs

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.
IEEE

Multi-Agent Evolutionary Reinforcement Learning Based on Cooperative Games

Abstract: Despite the significant advancements in single-agent evolutionary reinforcement learning, research exploring evolutionary reinforcement learning within multi-agent systems is still in its ...
blockchain

Gemini 3 Pro AI Model Enhances Accuracy with Multi-Step Reinforcement Learning and Massive Context Handling

According to Google DeepMind, Gemini 3 Pro leverages multi-step reinforcement learning to significantly improve accuracy and reduce hallucinations in AI-generated content. The model is designed to ...
Microsoft

Agent Lightning: Adding reinforcement learning to AI agents without code rewrites

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...
IEEE

Operation Optimization Decision-Making of Aluminum Electrolysis Process Using Offline Reinforcement Learning

Abstract: A common scenario in aluminum electrolysis process is that the collected dataset contains different behavioral policies and some risky policies, such industrial scenario brings new ...