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<atom:link href="https://llmrisks.github.io/index.xml" rel="self" type="application/rss+xml" />


<item>
<title>Week 7: GANs and DeepFakes</title>
<link>https://llmrisks.github.io/week7/</link>
<pubDate>Mon, 16 Oct 2023 00:00:00 +0000</pubDate>
<author>[email protected] (David Evans)</author>
<guid>https://llmrisks.github.io/week7/</guid>
<description>(see bottom for assigned readings and questions)
Presenting Team: Aparna Kishore, Elena Long, Erzhen Hu, Jingping Wan
Blogging Team: Haochen Liu, Haolin Liu, Ji Hyun Kim, Stephanie Schoch, Xueren Ge
Monday, 9 October: Generative Adversarial Networks and DeepFakes Today&#39;s topic is how to utilize generative adversarial networks to create fake images and how to identify the images generated by these models.
Generative Adversarial Network (GAN) is a revolutionary deep learning framework that pits two neural networks against each other in a creative showdown.</description>
</item>

<item>
<title>Week 5: Hallucination</title>
<link>https://llmrisks.github.io/week5/</link>
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<div class="row">


<h2><a href="/week7/">Week 7: GANs and DeepFakes</a></h2>
<div class="post-metadata">
<span class="post-date">
<time datetime="2023-10-16 00:00:00 &#43;0000 UTC" itemprop="datePublished">16 October 2023</time>
</span>

</div>


(see bottom for assigned readings and questions)
Presenting Team: Aparna Kishore, Elena Long, Erzhen Hu, Jingping Wan
Blogging Team: Haochen Liu, Haolin Liu, Ji Hyun Kim, Stephanie Schoch, Xueren Ge
Monday, 9 October: Generative Adversarial Networks and DeepFakes Today's topic is how to utilize generative adversarial networks to create fake images and how to identify the images generated by these models.
Generative Adversarial Network (GAN) is a revolutionary deep learning framework that pits two neural networks against each other in a creative showdown.
<p class="text-right"><a href="/week7/">Read More…</a></p>



<h2><a href="/week5/">Week 5: Hallucination</a></h2>
<div class="post-metadata">
<span class="post-date">
Expand Down Expand Up @@ -243,27 +261,13 @@ <h2><a href="/survey/">Welcome Survey</a></h2>



<h2><a href="/welcome/">Welcome to the LLM Risks Seminar</a></h2>
<div class="post-metadata">
<span class="post-date">
<time datetime="2023-05-26 00:00:00 &#43;0000 UTC" itemprop="datePublished">26 May 2023</time>
</span>

</div>


Full Transcript
Seminar Plan The actual seminar won&rsquo;t be fully planned by GPT-4, but more information on it won&rsquo;t be available until later.
I&rsquo;m expecting the structure and format to that combines aspects of this seminar on adversarial machine learning and this course on computing ethics, but with a topic focused on learning as much as we can about the potential for both good and harm from generative AI (including large language models) and things we can do (mostly technically, but including policy) to mitigate the harms.
<p class="text-right"><a href="/welcome/">Read More…</a></p>



<div class="row">
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<ul class="pagination" role="navigation" aria-label="Pagination">

<li><span>Page 1 of 1</span></li>
<li class="arrow" aria-disabled="true"><a href="/post/page/2/">&laquo; <em>Older<span class="show-for-sr"> blog entries</span></em></a></li>

<li><span>Page 1 of 2</span></li>

</ul>
All Posts by <a href="https://llmrisks.github.io/categories">Category</a> or <a href="https://llmrisks.github.io/tags">Tags</a>.
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<language>en-us</language>
<managingEditor>[email protected] (David Evans)</managingEditor>
<webMaster>[email protected] (David Evans)</webMaster>
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<item>
<title>Week 7: GANs and DeepFakes</title>
<link>https://llmrisks.github.io/week7/</link>
<pubDate>Mon, 16 Oct 2023 00:00:00 +0000</pubDate>
<author>[email protected] (David Evans)</author>
<guid>https://llmrisks.github.io/week7/</guid>
<description>(see bottom for assigned readings and questions)
Presenting Team: Aparna Kishore, Elena Long, Erzhen Hu, Jingping Wan
Blogging Team: Haochen Liu, Haolin Liu, Ji Hyun Kim, Stephanie Schoch, Xueren Ge
Monday, 9 October: Generative Adversarial Networks and DeepFakes Today&#39;s topic is how to utilize generative adversarial networks to create fake images and how to identify the images generated by these models.
Generative Adversarial Network (GAN) is a revolutionary deep learning framework that pits two neural networks against each other in a creative showdown.</description>
</item>

<item>
<title>Week 5: Hallucination</title>
<link>https://llmrisks.github.io/week5/</link>
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<h2><a href="/welcome/">Welcome to the LLM Risks Seminar</a></h2>
<div class="post-metadata">
<span class="post-date">
<time datetime="2023-05-26 00:00:00 &#43;0000 UTC" itemprop="datePublished">26 May 2023</time>
</span>

</div>


Full Transcript
Seminar Plan The actual seminar won&rsquo;t be fully planned by GPT-4, but more information on it won&rsquo;t be available until later.
I&rsquo;m expecting the structure and format to that combines aspects of this seminar on adversarial machine learning and this course on computing ethics, but with a topic focused on learning as much as we can about the potential for both good and harm from generative AI (including large language models) and things we can do (mostly technically, but including policy) to mitigate the harms.
<p class="text-right"><a href="/welcome/">Read More…</a></p>



<div class="row">
<div class="column small-12">
<ul class="pagination" role="navigation" aria-label="Pagination">

<li><span>Page 2 of 2</span></li>

<li class="arrow" aria-disabled="true"><a href="/post/"><em>Newer<span class="show-for-sr"> blog entries</span></em>:&nbsp;&raquo;</a></li>

</ul>
All Posts by <a href="https://llmrisks.github.io/categories">Category</a> or <a href="https://llmrisks.github.io/tags">Tags</a>.

</div>
</div>

</div>
</div>
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<a href="//llmrisks.github.io"><b>cs 6501: Risks (and Benefits) of Generative AI</b></a><br>
Fall 2023<br>
<a href="//www.cs.virginia.edu">University of Virginia</a>
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<url>
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+++
date = "16 Oct 2023"
draft = true
draft = false
title = "Week 7: GANs and DeepFakes"
slug = "week6"
slug = "week7"
+++

(see bottom for assigned readings and questions)
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<li class="arrow" aria-disabled="true"><a href="https://llmrisks.github.io/week4/">&laquo; <em>Previous<span class="show-for-sr"> page</span></em>: Week 4: Capabilities of LLMs</a></li>


<li class="arrow" aria-disabled="true"><a href="https://llmrisks.github.io/week7/"><em>Next<span class="show-for-sr"> page</span></em>: Week 7: GANs and DeepFakes&nbsp;&raquo;</a></li>

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