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  • Where Should Action Generation Begin? A Learnable Source Prior for . . .
    Abstract Generative robot policies typically begin action generation from an observation-independent standard Gaussian distribution, leaving the choice of source distribution underexplored This work asks a simple question: where should action generation begin?
  • Video Generators are Robot Policies - arXiv. org
    In this paper, we use video generation as a proxy for robot policy learning to address both limitations simultaneously We propose Video Policy, a modular framework that combines video and action generation that can be trained end-to-end
  • Inference-Time Enhancement of Generative Robot Policies via Predictive . . .
    From expert demonstrations, we train a diffusion-based policy that generates short-horizon action chunks conditioned on past observations, providing a generative prior over plausible behaviors
  • Yanjiang Guo
    Selected Research (* indicates equal contribution) Video World Model Vision-Language-Action Model LLM Agent, RL
  • GitHub - AbdelStark gpc_rs: Implementation of Generative Robot Policies . . .
    The demo TUI exposes the core stages of the pipeline: dataset generation, world-model warmup, diffusion-policy training, candidate rollout, ranking, and selected-action inspection
  • 最新World Model × （具身智能）Robotics论文解析--世界模型正在重塑机器人的大脑 - 知乎
    从研究版图看，ICLR 2025 专门设立 “World Models: Understanding, Modelling and Scaling” 与 “Generative Models for Robot Learning” 等工作坊，聚焦 embodied AI、视频世界模型与机器人控制，表明“世界建模”已被视为通往通用机器人与 AGI 的主线之一，而非边缘话题。
  • Guided Streaming Stochastic Interpolant Policy | alphaXiv
    Most state-of-the-art robot policies, such as Diffusion Policy, treat action generation as a "denoising" process The robot observes the environment, generates a fixed-length "chunk" of future actions (e g , the next 8 or 16 steps), and then begins execution
  • Generative Robot Policies - emergentmind. com
    Unlike conventional policies, which produce a single best action for each state, generative policies enable the exploration of a continuum of viable behaviors, crucial for robustness, sample efficiency, and generalization across tasks, embodiments, and environments
  • VLA之外，具身+VA工作汇总 - 知乎
    前面一直分享VLA相关工作，这里也为大家汇总下具身+VA相关的工作（ Vision + Action），涉及机器人操作、DP、全身控制、One-Shot 、sim2real、端到端等；内容出自具身智能之心知识星球！ 原文链接：VLA之外，具身+…
  • ICLR 2025 Papers
    CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code





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