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ophidian    
a. 蛇类的,蛇样的
n. 蛇



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  • World Action Models: The Next Frontier in Embodied AI
    We formally define WAMs and disambiguate them from related concepts, and trace the foundations and early integration of VLA and world model research that gave rise to this paradigm
  • World Action Models: The Next Frontier in Embodied AI
    This repository accompanies our survey on World Action Models (WAMs) — the emerging paradigm that unifies predictive world modeling with action generation for embodied AI
  • World Action Models: The Next Frontier in Embodied AI
    We term this emerging paradigm World Action Models (WAMs): embodied foundation models that unify predictive state modeling with action generation, targeting a joint distribution over future states and actions rather than actions alone
  • World Action Models: The Next Frontier in Embodied AI
    图 1:世界行动模型(WAM)代表性工作的时间演进与分类体系(Figure 1: Temporal evolution and taxonomy of representative works on World Action Models (WAMs))。左侧分支展示了联合式 WAM 架构的演进,这些架构将世界预测和动作生成紧密耦合,呈现出基于自回归(Autoregressive)和基于扩散(Diffusion-based)两种表示方案的
  • World Action Models: The Next Frontier in Embodied AI
    The paper investigates how embodied AI systems can be enhanced through World Action Models (WAMs) that unify predictive state modeling with action generation, addressing the limitation that Vision-Language-Action models lack explicit modeling of world dynamics
  • 【Frontier】具身智能的下一战!【World Action Model . . .
    【Frontier】 具身智能 的下一战!World Action Model 未来范式! 导语:2025 年底,Nvidia 机器人负责人 Jim Fan 在年度总结中写下了一句震动行业的话:“The next frontier of embodied AI is not more teleoperation data, not bigger VLA models — it’s World Action Models ” 2026 年 2 月,DreamZero 论文横空出世:14B 参数的 WAM,仅用 30
  • World Action Models: The Next Frontier in Embodied AI
    We formally define WAMs and disambiguate them from related concepts, and trace the foundations and early integration of VLA and world model research that gave rise to this paradigm
  • [论文评述] World Action Models: The Next Frontier in Embodied AI
    《World Action Models: The Next Frontier in Embodied AI》这篇综述深入探讨了具身人工智能领域新兴的“世界动作模型”(World Action Models, WAMs)范式。 传统 Vision-Language-Action (VLA) 模型在具身策略学习中实现了强大的语义泛化能力,但它们仅仅学习反应式的“观察-动作”映射,未能明确建模物理世界在干预下如何演变。 WAMs 通过将环境动态的预测模型(即世界模型)整合到动作生成流程中,弥补了这一局限性。 WAMs 是一种具身基础模型,它统一了预测状态建模和动作生成,目标是未来状态和动作的联合分布 $p (o', a | o, l)$,而不仅仅是动作本身。 2 定义与形式化





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