Qwen-AgentWorld: Language World Models for General Agents

Researchers introduced Qwen-AgentWorld, a framework for training general agents using language world models. This allows for more efficient and effective training of agents that can understand and interact with complex environments. The framework has potential applications in areas such as robotics and game playing. The paper is available on arXiv and has been discussed on Hacker News. Engineers may be interested in exploring the framework for their own projects.