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中文(ZH) ICML 2026世界模型研究盘点:LAWM VS WAM,谁主沉浮?

World Models at ICML 2026: LAWM and WAM converge for embodied AI

Research at ICML 2026 indicates a paradigm shift in world models, moving beyond simple video prediction towards real-world control. While Latent Action World Models (LAWM) provide foundational physical intuition from video, World Action Models (WAM) are seeing a resurgence for explicit control tasks. The emerging consensus favors a hybrid approach, using LAWM for broad pre-training and WAM for fine-tuning with real-world robot data, mirroring the success of large language models. AI

IMPACT Convergence of LAWM and WAM approaches signals a path toward more capable embodied AI agents that can interact with and control the physical world.

RANK_REASON The cluster discusses research trends and specific papers presented at a major academic conference (ICML 2026) concerning world models. [lever_c_demoted from research: ic=1 ai=1.0]

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World Models at ICML 2026: LAWM and WAM converge for embodied AI

COVERAGE [1]

  1. 雷峰网 (Leiphone) TIER_1 中文(ZH) ·

    ICML 2026 World Model Research Review: LAWM vs. WAM, Who Will Reign Supreme?

    <p>作为机器学习领域的顶级学术盛会,“世界模型”这一主题在ICML的接收论文名单中,从绝对数量上看似乎并不占上风。根据MTRI近日发布的一篇报告,在ICML 2026被接收的6341篇论文中,有49篇论文属于“世界模型”分类,占比不到1%。然而,在仔细剖析论文趋势并在大会现场与参会者深入交流后我们发现,今年的ICML世界模型研究正经历一场至关重要的范式革命。</p><p>在会场内外,学者们争论的核心焦点早已跳出“要不要用世界模型”的启蒙阶段,彻底演变为具体的技术路线选择:是沿着依赖显式动作数据的WAM(World Action Models)路线深耕,…