用潜在动作引导在线强化学习，让大模型从离线轨迹中提炼行动先验，训练更高效可控。
arXiv:2606.24669v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for planning and sequential decision-making, …
机器人策略学习新思路，PoLAR将潜在动作清晰分解为程度与模式，助力高效控制。
arXiv:2606.21139v1 Announce Type: cross Abstract: Latent action pretraining learns representations of visual change from pairs of observations, but ex…
世界模型赋能潜在动作预训练，探索更高效的智能体学习范式。
arXiv:2509.18428v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have gained popularity for learning robotic manipulation…
DiLA将潜在动作解耦为几何与纹理流，实现高保真视频预测，突破LAMs的抽象-保真权衡。
arXiv:2605.15725v1 Announce Type: cross Abstract: Latent Action Models (LAMs) enable the learning of world models from unlabeled video by inferring ab…