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OpenForgeRL reveals that decoupling training from inference can dramatically enhance the performance and reliability of AI agents in real-world applications.
OpenWebRL-4B sets a new benchmark for open-source visual web agents, achieving impressive success rates with minimal initial data while outperforming larger-scale competitors.
Autonomous web agents get a serious upgrade with WebXSkill, which lets them learn and execute skills with both code-level precision and human-readable guidance.
GUI agents can achieve significantly stronger task-solving capabilities through carefully designed post-training and data curation, without relying on costly online data collection.
Forget task-specific models: Magma, a single foundation model, now outperforms them in both UI navigation and robotic manipulation by bridging verbal and action abilities.
