Author

Baochang Ren

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#artificial intelligence Jan 2026

Aligning Agentic World Models via Knowledgeable Experience Learning

WorldMind is introduced, a framework that autonomously constructs a symbolic World Knowledge Repository by synthesizing environmental feedback that unifies Process Experience to enforce physical feasibility via prediction errors and Goal Experience to guide task optimality through successful trajectories.

Baochang Ren, Yunzhi Yao, Rui Sun et al. · arXiv.org · 3 citations · ⚡1

#artificial intelligence Preprint Sep 2025

OceanGym: A Benchmark Environment for Underwater Embodied Agents

OceanGym is introduced, the first comprehensive benchmark for ocean underwater embodied agents, designed to advance AI in one of the most demanding real-world environments, and reveals substantial gaps between state-of-the-art MLLM-driven agents and human experts.

Yida Xue, Mingjun Mao, Xiangyuan Ru et al. · 0 citations