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components/app-sidebar.tsx

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@@ -176,7 +176,10 @@ export function AppSidebar() {
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<Collapsible className="group/collapsible flex flex-col gap-6">
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<Link href="/projects" className="p-2 rounded-sm hover:bg-o-blue/3 select-none">
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Project
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</Link>
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{/* <Collapsible className="group/collapsible flex flex-col gap-6">
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<SidebarMenuItem>
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<CollapsibleTrigger className="w-full flex flex-row justify-between items-center p-2 rounded-sm hover:bg-o-blue/3 select-none">
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Project
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</SidebarMenuSub>
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</CollapsibleContent>
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</SidebarMenuItem>
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</Collapsible>
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</Collapsible> */}
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<Collapsible className="group/collapsible flex flex-col gap-6">
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<Link href="/publications" className="p-2 rounded-sm hover:bg-o-blue/3 select-none">
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Publication
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</Link>
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{/* <Collapsible className="group/collapsible flex flex-col gap-6">
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<SidebarMenuItem>
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<CollapsibleTrigger className="w-full flex flex-row justify-between items-center p-2 rounded-sm hover:bg-o-blue/3 select-none">
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Publication
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</SidebarMenuSub>
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</CollapsibleContent>
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</SidebarMenuItem>
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</Collapsible>
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</Collapsible> */}
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data/publications.tsx

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@@ -109,7 +109,7 @@ export const publications: {
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},
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],
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description: "A unified vision-language-action framework that enables policy learning across different environments.",
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keys: ['editor_pick', 'drawer_embodied', 'home_sliding'],
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keys: ['editor_pick', 'home_sliding', 'drawer_embodied'],
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},
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{
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title: "Planning-oriented Autonomous Driving",
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},
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],
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description: "UniAD: The first comprehensive framework that incorporates full-stack driving tasks.",
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keys: ['editor_pick', 'drawer_e2e', 'home_sliding'],
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keys: ['editor_pick', 'home_sliding', 'drawer_e2e'],
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},
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{
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title: "AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems",
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}
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],
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description: "A novel generalist policy that leverages latent action representations to maximize data utilization, demonstrating predictable performance scaling with increased data volume.",
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keys: ['editor_pick', 'home_sliding'],
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keys: ['editor_pick', 'home_sliding', 'drawer_embodied'],
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},
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{
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title: "End-to-End Autonomous Driving: Challenges and Frontiers",
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},
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],
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description: "In this survey, we provide a comprehensive analysis of more than 270 papers on the motivation, roadmap, methodology, challenges, and future trends in end-to-end autonomous driving.",
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keys: ['editor_pick', 'drawer_e2e', 'survey'],
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keys: ['editor_pick', 'survey', 'drawer_e2e'],
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},
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{
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title: "DriveLM: Driving with Graph Visual Question Answering",
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},
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],
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description: "Unlocking the future where autonomous driving meets the unlimited potential of language.",
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keys: ['editor_pick', 'home_sliding'],
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keys: ['editor_pick', 'home_sliding', 'drawer_e2e'],
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},
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{
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title: "FreeTacMan: Robot-free Visuo-Tactile Data Collection System for Contact-rich Manipulation",
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},
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],
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description: "We propose a general pre-training pipeline that learns Manipulation by Predicting the Interaction (MPI).",
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keys: ['embodied_ai', 'drawer_embodied'],
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keys: ['embodied_ai'],
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},
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{
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title: "MTGS: Multi-Traversal Gaussian Splatting",
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},
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],
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description: "ReSim is a driving world model that enables Reliable Simulation of diverse open-world driving scenarios under various actions, including hazardous non-expert ones. A Video2Reward model estimates the reward from ReSim's simulated future.",
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keys: ['end_to_end_ad', 'drawer_e2e', 'home_sliding'],
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keys: ['end_to_end_ad', 'home_sliding'],
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},
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{
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title: "ETA: Efficiency through Thinking Ahead, A Dual Approach to Self-Driving with Large Models",

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