Найден корректный robots.txt
Файл управления сканированием сайта роботами
?
Robots.txt указывает поисковым роботам, какие страницы сканировать, а какие — нет. Ошибки в файле могут случайно закрыть важные разделы от индексации.
Кол-во редиректов для файла robots.txt 3 слишком большое! Это может вызывать затруднение при индексации поисковыми роботами!
Проверяемая страница не запрещена в robots.txt.
Цепочка редиректов для файла robots.txt:
http://ruc-aim3.com/robots.txt
302 Found
http://www.ruc-aim3.com/
301 MovedPermanently
https://www.ruc-aim3.com/
200 OK
Показать содержимое robots.txt
<!DOCTYPE html>
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<head>
<meta charset="utf-8"/>
<title>AIM3 Lab</title>
<meta property="og:type" content="website"/>
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<link href="https://fonts.googleapis.com" rel="preconnect"/>
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<script type="text/javascript">
WebFont.load({
google: {
families: ["Inter:100,200,300,regular,500,600,700,800,900", "Lora:regular,500,600,700,italic,500italic,600italic,700italic"]
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!function(o, c) {
var n = c.documentElement
, t = " w-mod-";
n.className += t + "js",
("ontouchstart"in o || o.DocumentTouch && c instanceof DocumentTouch) && (n.className += t + "touch")
}(window, document);
</script>
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window.__WEBFLOW_CURRENCY_SETTINGS = {
"currencyCode": "USD",
"symbol": "$",
"decimal": ".",
"fractionDigits": 2,
"group": ",",
"template": "{{wf {\"path\":\"symbol\",\"type\":\"PlainText\"} }} {{wf {\"path\":\"amount\",\"type\":\"CommercePrice\"} }} {{wf {\"path\":\"currencyCode\",\"type\":\"PlainText\"} }}",
"hideDecimalForWholeNumbers": false
};
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<h1>Multi-level, Multi-aspect, Multi-modal</h1>
<p style="font-size: 18px !important;">We live in a multi-modal world, we learn, we think and we express through multiple modalities. Therefore for AI systems they should have the ability to understand the multi-modal world. <br>Our research efforts for building AI systems focus on understanding from multi-level, multi-aspect and multi-modal.</p>
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<h2 class="no-margins">AIM3 Research</h2>
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<div class="text-h3" style="font-size: 26px;">Vision, Audio & Language</div>
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<div class="body-2">Building deep learning models that can reason about images, videos, audio, and text.</div>
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<div class="text-h3" style="font-size: 26px;">3D & Embodied</div>
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<div class="body-2">Understanding and interacting with 3D environments and physical entities.</div>
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<div class="text-h3" style="font-size: 26px;">Affective & Social Computing</div>
<img src="assets/research_topics/emotion.png" loading="lazy" alt="" class="service-icon"/>
<div class="body-2">Modeling human emotions and social behaviors, and interpersonal dynamics via AI.</div>
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<div class="text-h3" style="font-size: 26px;">AI Safety</div>
<img src="assets/research_topics/ai_safety.png" loading="lazy" alt="" class="service-icon"/>
<div class="body-2">Ensure AI behave reliably, ethically, and aligned with human values.</div>
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<h2 class="no-margins">Demos</h2>
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<source src="assets/demo/demo.mp4" data-wf-ignore="true"/>
</video>
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<div class="text-h2">Awards</div>
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<div class="award">
<ul role="list">
<li>ACM Multimedia 2024 Honorable Mention Demo Award</li>
<li>2017-2024 TRECVID (Video to Text Description) Grand Challenge (Rank 1st)</li>
<li>3-5th CVPR/ECCV Affective Behavior Analysis in-the-wild (Rank 1st)</li>
<li>CVPR 2021 ActivityNet Entities Object Localization (Rank 1st)</li>
<li>2018-2020 CVPR “ActivityNet Dense Captioning Events in Videos” (Rank 1st)</li>
<li>CVPR 2020 The End-of-End-to-End A Video Understanding Pentathlon (Rank 2nd)</li>
<li>2017-2019 Audio-Visual Emotion Challenge (Rank 1st)</li>
<li>ICCV 2019 Outstanding Method Award in VATEX Video Captioning Challenge</li>
<li>2019 之江杯全球人工智能大赛视频内容描述生成 (第一名，30万元奖金)</li>
<li>CVPR 2019 ActivityNet Large Scale Activity Recognition Challenge (ANET) Temporal Captioning Task (Winner)</li>
<li>ACM Multimedia 2019 Audio-Visual Emotion Challenge (Winner)</li>
<li>CVPR 2018 ActivityNet Large Scale Activity Recognition Challenge (ANET) Temporal Captioning Task (Winner)</li>
<li>ACM Multimedia 2017 Best Grand Challenge Paper Award</li>
<li>2017 ACM Multimedia (Video to Language) Grand Challenge (Rank 1st)</li>
<li>2016 ACM Multimedia (Video to Language) Grand Challenge (Rank 1st)</li>
<li>2016 Audio-Visual Emotion Challenge (AVEC) (Rank 2nd)</li>
<li>2016 MediaEval Movie Emotion Impact Challenge (Rank 1st)</li>
<li>2016 Chinese Multimodal Emotion Challenge (MEC) (Rank 2nd)</li>
<li>2016 NLPCC Chinese Weibo Stance Detection (Rank 1st)</li>
<li>"Spoken English Assistant" system in IBM Bluemix computing contest (2nd Place Price)</li>
<li>2015 ImageCLEF (Image Sentence Generation) Evaluation (Rank 1st)</li>
</ul>
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