引用原文并解析 Qwen-AgentWorld 环境世界模型

feel like I'm missing the point here. I wired Qwen-AgentWorld-35B-A3B into an old web-simulation project just for vibe check. The results are fine, SERP page fine, page-link fine. but I don't get what makes this AgentWorld model special. Isn't this doable with any model? https://t.co/IRcxMmxBy4   > **引用原帖 Qwen (@Alibaba_Qwen):** > 📣📣 Meet Qwen-AgentWorld — a native language world model that simulates 7 agent environments (MCP, Search, Terminal, SWE, Web, OS, Android) within a single model. Environment modeling is the training objective from day one, not a post-hoc adaptation. > 🤔 LLMs are trained to be better agents — better at acting in environments. But nobody has trained them to model the environments themselves. > 🗺️ Our roadmap: investigate how language world modeling can push the boundaries of general agent capabilities, along two routes: > 1️⃣ Build a foundation model for environment simulation — outperforming Claude Opus 4.8 and GPT-5.4 on AgentWorldBench > 2️⃣ Investigate how world modeling enhances agent training: > 🔬 Controllable Sim RL (agentic RL with LWM as environments) surpasses training in real environments > 🧠 Learning to predict environments (LWM warm-up) makes agents stronger — remarkably, even without any agent-specific training, this predictive knowledge transfers to agentic tasks with zero fine-tuning > 📑 Paper: https://t.co/Jx2l5RKq71 > 📖 Blog: https://t.co/7tVcKyhsx2 > 💻 GitHub: https://t.co/B5Lvb1UZCn > 🤗 HuggingFace: https://t.co/Kw3QBL1TM5 > 🧩 ModelScope: https://t.co/YBnGYgMWWI > https://x.com/Alibaba_Qwen/status/2069720365442719867 Han Xiao (@hxiao): probably a wrong showcase but here's the source https://t.co/IpYwJxYPkT