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diff --git a/index.html b/index.html
diff --git a/index.xml b/index.xml
@@ -8,7 +8,23 @@
     <language>en-us</language>
     <managingEditor>[email protected] (David Evans)</managingEditor>
     <webMaster>[email protected] (David Evans)</webMaster>
-    <lastBuildDate>Mon, 30 Oct 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://llmrisks.github.io/index.xml" rel="self" type="application/rss+xml" />
+    <lastBuildDate>Wed, 23 Aug 2023 00:00:00 +0000</lastBuildDate>
+
+	<atom:link href="https://llmrisks.github.io/index.xml" rel="self" type="application/rss+xml" />
+
+
+    <item>
+      <title>Week 10: Data Selection for LLMs</title>
+      <link>https://llmrisks.github.io/week10/</link>
+      <pubDate>Fri, 03 Nov 2023 00:00:00 +0000</pubDate>
+      <author>[email protected] (David Evans)</author>
+      <guid>https://llmrisks.github.io/week10/</guid>
+      <description>(see bottom for assigned readings and questions)
+Presenting Team: Haolin Liu, Xueren Ge, Ji Hyun Kim, Stephanie Schoch 
+Blogging Team: Aparna Kishore, Elena Long, Erzhen Hu, Jingping Wan
+Monday, 30 October: Data Selection for Fine-tuning LLMs Question: Would more models help? We&amp;rsquo;ve discussed so many risks and issues of GenAI so far and one question is that it can be difficult for us to come up with a possible solution to these problems.</description>
+    </item>
+
     <item>
       <title>Week 9: Interpretability</title>
       <link>https://llmrisks.github.io/week9/</link>
@@ -100,7 +116,7 @@ Table of Contents  (Monday, 09/04/2023) Introduction to Alignment  Introduction
       <guid>https://llmrisks.github.io/week1/</guid>
       <description>(see bottom for assigned readings and questions)
 Attention, Transformers, and BERT Monday, 28 August
-Transformers1 are a class of deep learning models that have revolutionized the field of natural language processing (NLP) and various other domains. The concept of transformers originated as an attempt to address the limitations of traditional recurrent neural networks (RNNs) in sequential data processing. Here&amp;rsquo;s an overview of transformers&#39; evolution and significance.
+Transformers1 are a class of deep learning models that have revolutionized the field of natural language processing (NLP) and various other domains. The concept of transformers originated as an attempt to address the limitations of traditional recurrent neural networks (RNNs) in sequential data processing. Here&amp;rsquo;s an overview of transformers&amp;rsquo; evolution and significance.
 Background and Origin RNNs2 were one of the earliest models used for sequence-based tasks in machine learning.</description>
     </item>
 
@@ -218,4 +234,4 @@ I believe each team has at least a few members with enough experience using git
     </item>
 
   </channel>
-</rss>
+</rss>
diff --git a/post/index.html b/post/index.html
@@ -83,6 +83,23 @@
 <div class="row">
 
 
+    <h2><a href="/week10/">Week 10: Data Selection for LLMs</a></h2>
+<div class="post-metadata">
+  <span class="post-date">
+    <time datetime="2023-11-03 00:00:00 &#43;0000 UTC" itemprop="datePublished">3 November 2023</time>
+  </span>
+
+</div>
+
+
+(see bottom for assigned readings and questions)
+Presenting Team: Haolin Liu, Xueren Ge, Ji Hyun Kim, Stephanie Schoch 
+Blogging Team: Aparna Kishore, Elena Long, Erzhen Hu, Jingping Wan
+Monday, 30 October: Data Selection for Fine-tuning LLMs Question: Would more models help? We&rsquo;ve discussed so many risks and issues of GenAI so far and one question is that it can be difficult for us to come up with a possible solution to these problems.
+<p class="text-right"><a href="/week10/">Read More…</a></p>
+
+
+
     <h2><a href="/week9/">Week 9: Interpretability</a></h2>
 <div class="post-metadata">
   <span class="post-date">
@@ -212,7 +229,7 @@ <h2><a href="/week1/">Week 1: Introduction</a></h2>
 
 (see bottom for assigned readings and questions)
 Attention, Transformers, and BERT Monday, 28 August
-Transformers1 are a class of deep learning models that have revolutionized the field of natural language processing (NLP) and various other domains. The concept of transformers originated as an attempt to address the limitations of traditional recurrent neural networks (RNNs) in sequential data processing. Here&rsquo;s an overview of transformers' evolution and significance.
+Transformers1 are a class of deep learning models that have revolutionized the field of natural language processing (NLP) and various other domains. The concept of transformers originated as an attempt to address the limitations of traditional recurrent neural networks (RNNs) in sequential data processing. Here&rsquo;s an overview of transformers&rsquo; evolution and significance.
 Background and Origin RNNs2 were one of the earliest models used for sequence-based tasks in machine learning.
 <p class="text-right"><a href="/week1/">Read More…</a></p>
 
@@ -235,22 +252,6 @@ <h2><a href="/discussions/">Github Discussions</a></h2>
 
 
 
-    <h2><a href="/class0/">Class 0: Getting Organized</a></h2>
-<div class="post-metadata">
-  <span class="post-date">
-    <time datetime="2023-08-23 00:00:00 &#43;0000 UTC" itemprop="datePublished">23 August 2023</time>
-  </span>
-
-</div>
-
-
-I&rsquo;ve updated the Schedule and Bi-Weekly Schedule based on the discussions today.
-The plan is below:
-  Week Lead Team Blogging Team Everyone Else     Two Weeks Before  Come up with idea for the week and planned readings, send to me by 5:29pm on Tuesday (2 weeks - 1 day before)  -  -    Week Before  Post plan and questions in github discussions by no later than 9am Wednesday; prepare for leading meetings   Prepare plan for blogging (how you will divide workload, collaborative tools for taking notes and writing)   Read/do materials and respond to preparation questions in github discussions (by 5:29pm Sunday)    Week of Leading Meetings  Lead interesting, engaging, and illuminating meetings!
-<p class="text-right"><a href="/class0/">Read More…</a></p>
-
-
-
     <div class="row">
   <div class="column small-12">
     <ul class="pagination" role="navigation" aria-label="Pagination">

diff --git a/post/index.xml b/post/index.xml
@@ -8,7 +8,23 @@
     <language>en-us</language>
     <managingEditor>[email protected] (David Evans)</managingEditor>
     <webMaster>[email protected] (David Evans)</webMaster>
-    <lastBuildDate>Mon, 30 Oct 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://llmrisks.github.io/post/index.xml" rel="self" type="application/rss+xml" />
+    <lastBuildDate>Fri, 03 Nov 2023 00:00:00 +0000</lastBuildDate>
+
+	<atom:link href="https://llmrisks.github.io/post/index.xml" rel="self" type="application/rss+xml" />
+
+
+    <item>
+      <title>Week 10: Data Selection for LLMs</title>
+      <link>https://llmrisks.github.io/week10/</link>
+      <pubDate>Fri, 03 Nov 2023 00:00:00 +0000</pubDate>
+      <author>[email protected] (David Evans)</author>
+      <guid>https://llmrisks.github.io/week10/</guid>
+      <description>(see bottom for assigned readings and questions)
+Presenting Team: Haolin Liu, Xueren Ge, Ji Hyun Kim, Stephanie Schoch 
+Blogging Team: Aparna Kishore, Elena Long, Erzhen Hu, Jingping Wan
+Monday, 30 October: Data Selection for Fine-tuning LLMs Question: Would more models help? We&amp;rsquo;ve discussed so many risks and issues of GenAI so far and one question is that it can be difficult for us to come up with a possible solution to these problems.</description>
+    </item>
+
     <item>
       <title>Week 9: Interpretability</title>
       <link>https://llmrisks.github.io/week9/</link>
@@ -100,7 +116,7 @@ Table of Contents  (Monday, 09/04/2023) Introduction to Alignment  Introduction
       <guid>https://llmrisks.github.io/week1/</guid>
       <description>(see bottom for assigned readings and questions)
 Attention, Transformers, and BERT Monday, 28 August
-Transformers1 are a class of deep learning models that have revolutionized the field of natural language processing (NLP) and various other domains. The concept of transformers originated as an attempt to address the limitations of traditional recurrent neural networks (RNNs) in sequential data processing. Here&amp;rsquo;s an overview of transformers&#39; evolution and significance.
+Transformers1 are a class of deep learning models that have revolutionized the field of natural language processing (NLP) and various other domains. The concept of transformers originated as an attempt to address the limitations of traditional recurrent neural networks (RNNs) in sequential data processing. Here&amp;rsquo;s an overview of transformers&amp;rsquo; evolution and significance.
 Background and Origin RNNs2 were one of the earliest models used for sequence-based tasks in machine learning.</description>
     </item>
 
@@ -161,4 +177,4 @@ I&amp;rsquo;m expecting the structure and format to that combines aspects of thi
     </item>
 
   </channel>
-</rss>
+</rss>
diff --git a/post/page/2/index.html b/post/page/2/index.html
@@ -83,6 +83,22 @@
 <div class="row">
 
 
+    <h2><a href="/class0/">Class 0: Getting Organized</a></h2>
+<div class="post-metadata">
+  <span class="post-date">
+    <time datetime="2023-08-23 00:00:00 &#43;0000 UTC" itemprop="datePublished">23 August 2023</time>
+  </span>
+
+</div>
+
+
+I&rsquo;ve updated the Schedule and Bi-Weekly Schedule based on the discussions today.
+The plan is below:
+  Week Lead Team Blogging Team Everyone Else     Two Weeks Before  Come up with idea for the week and planned readings, send to me by 5:29pm on Tuesday (2 weeks - 1 day before)  -  -    Week Before  Post plan and questions in github discussions by no later than 9am Wednesday; prepare for leading meetings   Prepare plan for blogging (how you will divide workload, collaborative tools for taking notes and writing)   Read/do materials and respond to preparation questions in github discussions (by 5:29pm Sunday)    Week of Leading Meetings  Lead interesting, engaging, and illuminating meetings!
+<p class="text-right"><a href="/class0/">Read More…</a></p>
+
+
+
     <h2><a href="/updates/">Updates</a></h2>
 <div class="post-metadata">
   <span class="post-date">

diff --git a/readings/index.html b/readings/index.html
@@ -144,14 +144,14 @@ <h2 id="fairness-and-bias">Fairness and Bias</h2>
 <p>Shangbin Feng, Chan Young Park, Yuhan Liu, Yulia Tsvetkov. <a href="https://arxiv.org/abs/2305.08283"><em>From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models</em></a>. ACL 2023.</p>
 <p>Myra Cheng, Esin Durmus, Dan Jurafsky. <a href="https://arxiv.org/abs/2305.18189"><em>Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models</em></a>. ACL 2023.</p>
 <h2 id="alignment">&ldquo;Alignment&rdquo;</h2>
-<p>Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li. <a href="https://arxiv.org/abs/2308.05374"><em>Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment</em></a>. <a href="https://arxiv.org/abs/2308.05374">https://arxiv.org/abs/2308.05374</a>.</p>
+<p>Yang Liu, Yuanshun Yao, Jean-Francois Ton, Xiaoying Zhang, Ruocheng Guo Hao Cheng, Yegor Klochkov, Muhammad Faaiz Taufiq, Hang Li. <a href="https://arxiv.org/abs/2308.05374"><em>Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models&rsquo; Alignment</em></a>. <a href="https://arxiv.org/abs/2308.05374">https://arxiv.org/abs/2308.05374</a>.</p>
 <h2 id="agi">AGI</h2>
 <p>Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, Yi Zhang. <a href="https://www.microsoft.com/en-us/research/publication/sparks-of-artificial-general-intelligence-early-experiments-with-gpt-4/"><em>Sparks of Artificial General Intelligence: Early experiments with GPT-4</em></a>. Microsoft, March 2023. <a href="https://arxiv.org/abs/2303.12712">https://arxiv.org/abs/2303.12712</a></p>
 <p>Yejin Choi. <a href="https://www.amacad.org/publication/curious-case-commonsense-intelligence"><em>The Curious Case of Commonsense Intelligence</em></a>. Daedalus, Spring 2022.</p>
 <p>Konstantine Arkoudas. <a href="https://arxiv.org/abs/2308.03762"><em>GPT-4 Can&rsquo;t Reason</em></a>. <a href="https://arxiv.org/abs/2308.03762">https://arxiv.org/abs/2308.03762</a>.</p>
 <p>Natalie Shapira, Mosh Levy, Seyed Hossein Alavi, Xuhui Zhou, Yejin Choi, Yoav Goldberg, Maarten Sap, Vered Shwartz. <a href="https://arxiv.org/abs/2305.14763"><em>Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models</em></a>.</p>
 <p>Melanie Sclar, Sachin Kumar, Peter West, Alane Suhr, Yejin Choi, Yulia
-Tsvetkov. <a href="https://arxiv.org/abs/2306.00924"><em>Minding Language Models' (Lack of) Theory of Mind: A
+Tsvetkov. <a href="https://arxiv.org/abs/2306.00924"><em>Minding Language Models&rsquo; (Lack of) Theory of Mind: A
 Plug-and-Play Multi-Character Belief
 Tracker</em></a>. ACL 2023</p>
 <p>Boaz Barak. <a href="https://windowsontheory.org/2023/07/17/the-shape-of-agi-cartoons-and-back-of-envelope/"><em>The shape of AGI: Cartoons and back of envelope</em></a>. July 2023.</p>

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@@ -1,68 +1,117 @@
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+
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-    <lastmod>2023-10-30T00:00:00+00:00</lastmod>
-  </url><url>
-    <loc>https://llmrisks.github.io/</loc>
-    <lastmod>2023-10-30T00:00:00+00:00</lastmod>
-  </url><url>
+    <lastmod>2023-11-03T00:00:00+00:00</lastmod>
+  </url>
+
+  <url>
+    <loc>https://llmrisks.github.io/week10/</loc>
+    <lastmod>2023-11-03T00:00:00+00:00</lastmod>
+  </url>
+
+  <url>
     <loc>https://llmrisks.github.io/week9/</loc>
     <lastmod>2023-10-30T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
+
+  <url>
     <loc>https://llmrisks.github.io/week8/</loc>
     <lastmod>2023-10-22T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
+
+  <url>
     <loc>https://llmrisks.github.io/week7/</loc>
     <lastmod>2023-10-16T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/week5/</loc>
     <lastmod>2023-10-04T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/week4/</loc>
     <lastmod>2023-09-25T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/week3/</loc>
     <lastmod>2023-09-18T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/week2/</loc>
     <lastmod>2023-09-11T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/week1/</loc>
     <lastmod>2023-09-03T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/discussions/</loc>
     <lastmod>2023-08-25T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/class0/</loc>
     <lastmod>2023-08-23T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
+
+  <url>
+    <loc>https://llmrisks.github.io/</loc>
+    <lastmod>2023-08-23T00:00:00+00:00</lastmod>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/weeklyschedule/</loc>
     <lastmod>2023-08-23T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
+
+  <url>
     <loc>https://llmrisks.github.io/readings/</loc>
     <lastmod>2023-08-21T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
+
+  <url>
     <loc>https://llmrisks.github.io/schedule/</loc>
     <lastmod>2023-08-21T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
+
+  <url>
     <loc>https://llmrisks.github.io/updates/</loc>
     <lastmod>2023-08-21T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/survey/</loc>
     <lastmod>2023-08-17T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/welcome/</loc>
     <lastmod>2023-05-26T00:00:00+00:00</lastmod>
-  </url><url>
+  </url>
+
+  <url>
     <loc>https://llmrisks.github.io/syllabus/</loc>
     <priority>0</priority>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/blogging/</loc>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/tags/</loc>
-  </url><url>
+  </url>
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+  <url>
     <loc>https://llmrisks.github.io/topics/</loc>
   </url>
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+</urlset>