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diff --git a/content/docs/hybridbatch.pdf b/content/docs/hybridbatch.pdf
diff --git a/content/main.md b/content/main.md
@@ -54,7 +54,9 @@ Reducing the search space for adversaries by coalescing inputs.<br>
 
 ## Papers
 
-Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. [_Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness_](/docs/empirically-measuring-concentration.pdf). In [_NeurIPS 2019_](https://nips.cc/Conferences/2019/). Vancouver, December 2019. (Earlier versions appeared in [_Debugging Machine Learning Models_](https://debug-ml-iclr2019.github.io/) and [_Safe Machine Learning: Specification, Robustness and Assurance_](https://sites.google.com/view/safeml-iclr2019), workshops attached to m>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [[PDF](/docs/empirically-measuring-concentration.pdf)] [[Post](https://jeffersonswheel.org/empirically-measuring-concentration/)]
+Fnu Suya, Jianfeng Chi, David Evans, and Yuan Tian. [_Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries_](/docs/hybridbatch.pdf). In [_29<sup>th</sup> USENIX Security Symposium_](https://www.usenix.org/conference/usenixsecurity20). Boston, MA. August 12&ndash;14, 2020. [[PDF](/docs/hybridbatch.pdf)] [[ArXiV](https://arxiv.org/abs/1908.07000)] [[Code](https://github.com/suyeecav/Hybrid-Attack)]
+
+Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. [_Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness_](/docs/empirically-measuring-concentration.pdf). In [_NeurIPS 2019_](https://nips.cc/Conferences/2019/). Vancouver, December 2019. (Earlier versions appeared in [_Debugging Machine Learning Models_](https://debug-ml-iclr2019.github.io/) and [_Safe Machine Learning: Specification, Robustness and Assurance_](https://sites.google.com/view/safeml-iclr2019), workshops attached to m>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [[PDF](/docs/empirically-measuring-concentration.pdf)] [[Post](https://jeffersonswheel.org/empirically-measuring-concentration/)] [[Code](https://github.com/xiaozhanguva/Measure-Concentration)]
 
 Xiao Zhang and David Evans. [_Cost-Sensitive Robustness against Adversarial Examples_](/docs/cost-sensitive-robustness.pdf). In <a
 href="https://iclr.cc/Conferences/2019"><em>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="https://arxiv.org/abs/1810.09225">arXiv</a>] [<a

diff --git a/content/papers.md b/content/papers.md
@@ -2,8 +2,9 @@
 title = "Papers"
 +++
 
-Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. [_Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness_](/docs/empirically-measuring-concentration.pdf). In [_NeurIPS 2019_](https://nips.cc/Conferences/2019/). Vancouver, December 2019. (Earlier versions appeared in [_Debugging Machine Learning Models_](https://debug-ml-iclr2019.github.io/) and [_Safe Machine Learning: Specification, Robustness and Assurance_](https://sites.google.com/view/safeml-iclr2019), workshops attached to m>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [[PDF](/docs/empirically-measuring-concentration.pdf)] [[Post](https://jeffersonswheel.org/empirically-measuring-concentration/)]
+Fnu Suya, Jianfeng Chi, David Evans, and Yuan Tian. [_Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries_](/docs/hybridbatch.pdf). In [_29<sup>th</sup> USENIX Security Symposium_](https://www.usenix.org/conference/usenixsecurity20). Boston, MA. August 12&ndash;14, 2020. [[PDF](/docs/hybridbatch.pdf)] [[ArXiV](https://arxiv.org/abs/1908.07000)] [[Code](https://github.com/suyeecav/Hybrid-Attack)]
 
+Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. [_Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness_](/docs/empirically-measuring-concentration.pdf). In [_NeurIPS 2019_](https://nips.cc/Conferences/2019/). Vancouver, December 2019. (Earlier versions appeared in [_Debugging Machine Learning Models_](https://debug-ml-iclr2019.github.io/) and [_Safe Machine Learning: Specification, Robustness and Assurance_](https://sites.google.com/view/safeml-iclr2019), workshops attached to m>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [[PDF](/docs/empirically-measuring-concentration.pdf)] [[Post](https://jeffersonswheel.org/empirically-measuring-concentration/)] [[Code](https://github.com/xiaozhanguva/Measure-Concentration)]
 
 Xiao Zhang and David Evans. [_Cost-Sensitive Robustness against Adversarial Examples_](/docs/cost-sensitive-robustness.pdf). In <a
 href="https://iclr.cc/Conferences/2019"><em>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="https://arxiv.org/abs/1810.09225">arXiv</a>] [<a

diff --git a/public/docs/hybridbatch.pdf b/public/docs/hybridbatch.pdf
diff --git a/public/index.html b/public/index.html
@@ -150,7 +150,9 @@ <h2 id="projects">Projects</h2>
 
 <h2 id="papers">Papers</h2>
 
-<p>Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. <a href="/docs/empirically-measuring-concentration.pdf"><em>Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness</em></a>. In <a href="https://nips.cc/Conferences/2019/"><em>NeurIPS 2019</em></a>. Vancouver, December 2019. (Earlier versions appeared in <a href="https://debug-ml-iclr2019.github.io/"><em>Debugging Machine Learning Models</em></a> and <a href="https://sites.google.com/view/safeml-iclr2019"><em>Safe Machine Learning: Specification, Robustness and Assurance</em></a>, workshops attached to m&gt;Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="/docs/empirically-measuring-concentration.pdf">PDF</a>] [<a href="https://jeffersonswheel.org/empirically-measuring-concentration/">Post</a>]</p>
+<p>Fnu Suya, Jianfeng Chi, David Evans, and Yuan Tian. <a href="/docs/hybridbatch.pdf"><em>Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries</em></a>. In <a href="https://www.usenix.org/conference/usenixsecurity20"><em>29<sup>th</sup> USENIX Security Symposium</em></a>. Boston, MA. August 12&ndash;14, 2020. [<a href="/docs/hybridbatch.pdf">PDF</a>] [<a href="https://arxiv.org/abs/1908.07000">ArXiV</a>] [<a href="https://github.com/suyeecav/Hybrid-Attack">Code</a>]</p>
+
+<p>Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. <a href="/docs/empirically-measuring-concentration.pdf"><em>Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness</em></a>. In <a href="https://nips.cc/Conferences/2019/"><em>NeurIPS 2019</em></a>. Vancouver, December 2019. (Earlier versions appeared in <a href="https://debug-ml-iclr2019.github.io/"><em>Debugging Machine Learning Models</em></a> and <a href="https://sites.google.com/view/safeml-iclr2019"><em>Safe Machine Learning: Specification, Robustness and Assurance</em></a>, workshops attached to m&gt;Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="/docs/empirically-measuring-concentration.pdf">PDF</a>] [<a href="https://jeffersonswheel.org/empirically-measuring-concentration/">Post</a>] [<a href="https://github.com/xiaozhanguva/Measure-Concentration">Code</a>]</p>
 
 <p>Xiao Zhang and David Evans. <a href="/docs/cost-sensitive-robustness.pdf"><em>Cost-Sensitive Robustness against Adversarial Examples</em></a>. In <a
 href="https://iclr.cc/Conferences/2019"><em>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="https://arxiv.org/abs/1810.09225">arXiv</a>] [<a

diff --git a/public/index.xml b/public/index.xml
@@ -161,7 +161,9 @@ Reducing the search space for adversaries by coalescing inputs.&lt;br&gt;
 
 &lt;h2 id=&#34;papers&#34;&gt;Papers&lt;/h2&gt;
 
-&lt;p&gt;Saeed Mahloujifar&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Xiao Zhang&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Mohammad Mahmooday, and David Evans. &lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;&lt;em&gt;Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness&lt;/em&gt;&lt;/a&gt;. In &lt;a href=&#34;https://nips.cc/Conferences/2019/&#34;&gt;&lt;em&gt;NeurIPS 2019&lt;/em&gt;&lt;/a&gt;. Vancouver, December 2019. (Earlier versions appeared in &lt;a href=&#34;https://debug-ml-iclr2019.github.io/&#34;&gt;&lt;em&gt;Debugging Machine Learning Models&lt;/em&gt;&lt;/a&gt; and &lt;a href=&#34;https://sites.google.com/view/safeml-iclr2019&#34;&gt;&lt;em&gt;Safe Machine Learning: Specification, Robustness and Assurance&lt;/em&gt;&lt;/a&gt;, workshops attached to m&amp;gt;Seventh International Conference on Learning Representations&lt;/em&gt;&lt;/a&gt; (ICLR). New Orleans. May 2019. [&lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;PDF&lt;/a&gt;] [&lt;a href=&#34;https://jeffersonswheel.org/empirically-measuring-concentration/&#34;&gt;Post&lt;/a&gt;]&lt;/p&gt;
+&lt;p&gt;Fnu Suya, Jianfeng Chi, David Evans, and Yuan Tian. &lt;a href=&#34;//evademl.org/docs/hybridbatch.pdf&#34;&gt;&lt;em&gt;Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries&lt;/em&gt;&lt;/a&gt;. In &lt;a href=&#34;https://www.usenix.org/conference/usenixsecurity20&#34;&gt;&lt;em&gt;29&lt;sup&gt;th&lt;/sup&gt; USENIX Security Symposium&lt;/em&gt;&lt;/a&gt;. Boston, MA. August 12&amp;ndash;14, 2020. [&lt;a href=&#34;//evademl.org/docs/hybridbatch.pdf&#34;&gt;PDF&lt;/a&gt;] [&lt;a href=&#34;https://arxiv.org/abs/1908.07000&#34;&gt;ArXiV&lt;/a&gt;] [&lt;a href=&#34;https://github.com/suyeecav/Hybrid-Attack&#34;&gt;Code&lt;/a&gt;]&lt;/p&gt;
+
+&lt;p&gt;Saeed Mahloujifar&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Xiao Zhang&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Mohammad Mahmooday, and David Evans. &lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;&lt;em&gt;Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness&lt;/em&gt;&lt;/a&gt;. In &lt;a href=&#34;https://nips.cc/Conferences/2019/&#34;&gt;&lt;em&gt;NeurIPS 2019&lt;/em&gt;&lt;/a&gt;. Vancouver, December 2019. (Earlier versions appeared in &lt;a href=&#34;https://debug-ml-iclr2019.github.io/&#34;&gt;&lt;em&gt;Debugging Machine Learning Models&lt;/em&gt;&lt;/a&gt; and &lt;a href=&#34;https://sites.google.com/view/safeml-iclr2019&#34;&gt;&lt;em&gt;Safe Machine Learning: Specification, Robustness and Assurance&lt;/em&gt;&lt;/a&gt;, workshops attached to m&amp;gt;Seventh International Conference on Learning Representations&lt;/em&gt;&lt;/a&gt; (ICLR). New Orleans. May 2019. [&lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;PDF&lt;/a&gt;] [&lt;a href=&#34;https://jeffersonswheel.org/empirically-measuring-concentration/&#34;&gt;Post&lt;/a&gt;] [&lt;a href=&#34;https://github.com/xiaozhanguva/Measure-Concentration&#34;&gt;Code&lt;/a&gt;]&lt;/p&gt;
 
 &lt;p&gt;Xiao Zhang and David Evans. &lt;a href=&#34;//evademl.org/docs/cost-sensitive-robustness.pdf&#34;&gt;&lt;em&gt;Cost-Sensitive Robustness against Adversarial Examples&lt;/em&gt;&lt;/a&gt;. In &lt;a
 href=&#34;https://iclr.cc/Conferences/2019&#34;&gt;&lt;em&gt;Seventh International Conference on Learning Representations&lt;/em&gt;&lt;/a&gt; (ICLR). New Orleans. May 2019. [&lt;a href=&#34;https://arxiv.org/abs/1810.09225&#34;&gt;arXiv&lt;/a&gt;] [&lt;a
@@ -311,7 +313,9 @@ the detection accuracy is 99.74% (only 22 out of 5000 fast positives).&lt;/p&gt;
       <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
 
       <guid>//evademl.org/papers/</guid>
-      <description>&lt;p&gt;Saeed Mahloujifar&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Xiao Zhang&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Mohammad Mahmooday, and David Evans. &lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;&lt;em&gt;Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness&lt;/em&gt;&lt;/a&gt;. In &lt;a href=&#34;https://nips.cc/Conferences/2019/&#34;&gt;&lt;em&gt;NeurIPS 2019&lt;/em&gt;&lt;/a&gt;. Vancouver, December 2019. (Earlier versions appeared in &lt;a href=&#34;https://debug-ml-iclr2019.github.io/&#34;&gt;&lt;em&gt;Debugging Machine Learning Models&lt;/em&gt;&lt;/a&gt; and &lt;a href=&#34;https://sites.google.com/view/safeml-iclr2019&#34;&gt;&lt;em&gt;Safe Machine Learning: Specification, Robustness and Assurance&lt;/em&gt;&lt;/a&gt;, workshops attached to m&amp;gt;Seventh International Conference on Learning Representations&lt;/em&gt;&lt;/a&gt; (ICLR). New Orleans. May 2019. [&lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;PDF&lt;/a&gt;] [&lt;a href=&#34;https://jeffersonswheel.org/empirically-measuring-concentration/&#34;&gt;Post&lt;/a&gt;]&lt;/p&gt;
+      <description>&lt;p&gt;Fnu Suya, Jianfeng Chi, David Evans, and Yuan Tian. &lt;a href=&#34;//evademl.org/docs/hybridbatch.pdf&#34;&gt;&lt;em&gt;Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries&lt;/em&gt;&lt;/a&gt;. In &lt;a href=&#34;https://www.usenix.org/conference/usenixsecurity20&#34;&gt;&lt;em&gt;29&lt;sup&gt;th&lt;/sup&gt; USENIX Security Symposium&lt;/em&gt;&lt;/a&gt;. Boston, MA. August 12&amp;ndash;14, 2020. [&lt;a href=&#34;//evademl.org/docs/hybridbatch.pdf&#34;&gt;PDF&lt;/a&gt;] [&lt;a href=&#34;https://arxiv.org/abs/1908.07000&#34;&gt;ArXiV&lt;/a&gt;] [&lt;a href=&#34;https://github.com/suyeecav/Hybrid-Attack&#34;&gt;Code&lt;/a&gt;]&lt;/p&gt;
+
+&lt;p&gt;Saeed Mahloujifar&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Xiao Zhang&lt;sup&gt;&lt;font size=&#34;-2&#34;&gt;&amp;#9733;&lt;/font&gt;&lt;/sup&gt;, Mohammad Mahmooday, and David Evans. &lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;&lt;em&gt;Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness&lt;/em&gt;&lt;/a&gt;. In &lt;a href=&#34;https://nips.cc/Conferences/2019/&#34;&gt;&lt;em&gt;NeurIPS 2019&lt;/em&gt;&lt;/a&gt;. Vancouver, December 2019. (Earlier versions appeared in &lt;a href=&#34;https://debug-ml-iclr2019.github.io/&#34;&gt;&lt;em&gt;Debugging Machine Learning Models&lt;/em&gt;&lt;/a&gt; and &lt;a href=&#34;https://sites.google.com/view/safeml-iclr2019&#34;&gt;&lt;em&gt;Safe Machine Learning: Specification, Robustness and Assurance&lt;/em&gt;&lt;/a&gt;, workshops attached to m&amp;gt;Seventh International Conference on Learning Representations&lt;/em&gt;&lt;/a&gt; (ICLR). New Orleans. May 2019. [&lt;a href=&#34;//evademl.org/docs/empirically-measuring-concentration.pdf&#34;&gt;PDF&lt;/a&gt;] [&lt;a href=&#34;https://jeffersonswheel.org/empirically-measuring-concentration/&#34;&gt;Post&lt;/a&gt;] [&lt;a href=&#34;https://github.com/xiaozhanguva/Measure-Concentration&#34;&gt;Code&lt;/a&gt;]&lt;/p&gt;
 
 &lt;p&gt;Xiao Zhang and David Evans. &lt;a href=&#34;//evademl.org/docs/cost-sensitive-robustness.pdf&#34;&gt;&lt;em&gt;Cost-Sensitive Robustness against Adversarial Examples&lt;/em&gt;&lt;/a&gt;. In &lt;a
 href=&#34;https://iclr.cc/Conferences/2019&#34;&gt;&lt;em&gt;Seventh International Conference on Learning Representations&lt;/em&gt;&lt;/a&gt; (ICLR). New Orleans. May 2019. [&lt;a href=&#34;https://arxiv.org/abs/1810.09225&#34;&gt;arXiv&lt;/a&gt;] [&lt;a

diff --git a/public/main/index.html b/public/main/index.html
@@ -163,7 +163,9 @@ <h2 id="projects">Projects</h2>
 
 <h2 id="papers">Papers</h2>
 
-<p>Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. <a href="/docs/empirically-measuring-concentration.pdf"><em>Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness</em></a>. In <a href="https://nips.cc/Conferences/2019/"><em>NeurIPS 2019</em></a>. Vancouver, December 2019. (Earlier versions appeared in <a href="https://debug-ml-iclr2019.github.io/"><em>Debugging Machine Learning Models</em></a> and <a href="https://sites.google.com/view/safeml-iclr2019"><em>Safe Machine Learning: Specification, Robustness and Assurance</em></a>, workshops attached to m&gt;Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="/docs/empirically-measuring-concentration.pdf">PDF</a>] [<a href="https://jeffersonswheel.org/empirically-measuring-concentration/">Post</a>]</p>
+<p>Fnu Suya, Jianfeng Chi, David Evans, and Yuan Tian. <a href="/docs/hybridbatch.pdf"><em>Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries</em></a>. In <a href="https://www.usenix.org/conference/usenixsecurity20"><em>29<sup>th</sup> USENIX Security Symposium</em></a>. Boston, MA. August 12&ndash;14, 2020. [<a href="/docs/hybridbatch.pdf">PDF</a>] [<a href="https://arxiv.org/abs/1908.07000">ArXiV</a>] [<a href="https://github.com/suyeecav/Hybrid-Attack">Code</a>]</p>
+
+<p>Saeed Mahloujifar<sup><font size="-2">&#9733;</font></sup>, Xiao Zhang<sup><font size="-2">&#9733;</font></sup>, Mohammad Mahmooday, and David Evans. <a href="/docs/empirically-measuring-concentration.pdf"><em>Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness</em></a>. In <a href="https://nips.cc/Conferences/2019/"><em>NeurIPS 2019</em></a>. Vancouver, December 2019. (Earlier versions appeared in <a href="https://debug-ml-iclr2019.github.io/"><em>Debugging Machine Learning Models</em></a> and <a href="https://sites.google.com/view/safeml-iclr2019"><em>Safe Machine Learning: Specification, Robustness and Assurance</em></a>, workshops attached to m&gt;Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="/docs/empirically-measuring-concentration.pdf">PDF</a>] [<a href="https://jeffersonswheel.org/empirically-measuring-concentration/">Post</a>] [<a href="https://github.com/xiaozhanguva/Measure-Concentration">Code</a>]</p>
 
 <p>Xiao Zhang and David Evans. <a href="/docs/cost-sensitive-robustness.pdf"><em>Cost-Sensitive Robustness against Adversarial Examples</em></a>. In <a
 href="https://iclr.cc/Conferences/2019"><em>Seventh International Conference on Learning Representations</em></a> (ICLR). New Orleans. May 2019. [<a href="https://arxiv.org/abs/1810.09225">arXiv</a>] [<a