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‎app/(default)/(event)/cvpr2026/workshop/page.tsx‎

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<p className="leading-relaxed">
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If you are interested in our workshop, please <span className="underline">mark the workshop in your CVPR registration</span>, to have enough space for the workshop room.
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</p>
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<div className="mt-6">
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<img src="/assets/icon/discord.png" className="size-8 inline-block mr-2"/>
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<span>
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<Link href="https://discord.gg/pS74Qcp2SX" target="_blank" className="text-o-blue animated-underline">
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Join Discord
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</Link>
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<span>&nbsp;</span>to chat with the organizers.
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</span>
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</div>
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</div>
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</div>
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‎app/(default)/(event)/rss2026/workshop/page.tsx‎

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<p className="leading-relaxed">
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Recent progress in robot learning has significantly advanced robotic capabilities on short-horizon skills and well-defined tasks. However, despite these advances, robots, such as humanoids and robotic arms, continue to struggle when deployed on <span className="underline">long-horizon, complex tasks in the real world</span>. Topics of interest of this workshop include on-policy progress estimation for multi-stage tasks, run-time failure recovery, hierarchical and memory-augmented policies trained under long-horizon rollouts, sim-to-real transfer with execution-time fine-tuning, and leveraging foundation models for task planning, perception, and feedback within closed-loop, on-policy execution.
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</p>
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<div className="mt-6">
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<img src="/assets/icon/discord.png" className="size-8 inline-block mr-2"/>
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<span>
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<Link href="https://discord.gg/AQ3ESj7tvr" target="_blank" className="text-o-blue animated-underline">
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Join Discord
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</Link>
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<span>&nbsp;</span>to chat with the organizers.
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</span>
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</div>
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</div>
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</div>
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