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<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link
rel="icon"
href="data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'%3E%3Crect width='100' height='100' rx='20' fill='%236d28d9'/%3E%3Cg fill='none' stroke='white' stroke-width='6' stroke-linecap='round'%3E%3Crect x='24' y='30' width='52' height='40' rx='9'/%3E%3Cpath d='M24 30 18 22M76 30 82 22'/%3E%3C/g%3E%3Ccircle cx='50' cy='50' r='12' fill='none' stroke='white' stroke-width='6'/%3E%3Ccircle cx='50' cy='50' r='4' fill='white'/%3E%3C/svg%3E"
/>
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>RoboVista | Evaluating Vision-Language Models for Diverse Robot Applications</title>
<meta name="description" content="RoboVista is an expert-annotated, robot-centric Visual Question Answering benchmark with 474 questions across 6 robot application domains and 39 task types, built with the modular Robot Question Answering (RQA) framework." />
<meta name="keywords" content="RoboVista, RQA, Robot Question Answering, VQA, vision-language models, VLM, robot benchmark, embodied reasoning, surgical robotics, agricultural robotics, industrial automation, autonomous driving" />
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<meta property="og:title" content="RoboVista: Evaluating Vision-Language Models for Diverse Robot Applications" />
<meta property="og:description" content="A modular Robot Question Answering (RQA) framework and an expert-annotated 474-question benchmark spanning agricultural, industrial, domestic, surgical, driving, and open robot domains." />
<meta property="og:url" content="https://berkeleyautomation.github.io/robovista/" />
<meta property="og:image" content="https://berkeleyautomation.github.io/robovista/static/images/teaser-rqa.png" />
<meta property="og:type" content="website" />
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<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:title" content="RoboVista: Evaluating VLMs for Diverse Robot Applications" />
<meta name="twitter:description" content="Expert-annotated robot-centric VQA benchmark across 6 robot application domains, revealing substantial gaps in state-of-the-art VLMs." />
<meta name="twitter:image" content="https://berkeleyautomation.github.io/robovista/static/images/teaser-rqa.png" />
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<body>
<div id="root"></div>
<script type="module" src="/src/main.jsx"></script>
</body>
</html>