Add plenary talk data to XML files

data/xml/2021.acl.xml

@@ -12689,6 +12689,15 @@
       <url hash="8e86a5da">2021.acl-tutorials.1</url>
       <doi>10.18653/v1/2021.acl-tutorials.1</doi>
       <bibkey>bar-haim-etal-2021-advances</bibkey>
+      <video href="2021.acl-tutorials.1.1.mp4"/>
+      <video href="2021.acl-tutorials.1.2.mp4"/>
+      <video href="2021.acl-tutorials.1.3.mp4"/>
+      <video href="2021.acl-tutorials.1.4.mp4"/>
+      <video href="2021.acl-tutorials.1.5.mp4"/>
+      <video href="2021.acl-tutorials.1.6.mp4"/>
+      <video href="2021.acl-tutorials.1.7.mp4"/>
+      <video href="2021.acl-tutorials.1.8.mp4"/>
+      <video href="2021.acl-tutorials.1.9.mp4"/>
     </paper>
     <paper id="2">
       <title>Event-Centric Natural Language Processing</title>
@@ -12704,6 +12713,7 @@
       <url hash="d82826b3">2021.acl-tutorials.2</url>
       <doi>10.18653/v1/2021.acl-tutorials.2</doi>
       <bibkey>chen-etal-2021-event</bibkey>
+      <video href="2021.acl-tutorials.2.mp4"/>
     </paper>
     <paper id="3">
       <title>Meta Learning and Its Applications to Natural Language Processing</title>
@@ -12725,6 +12735,9 @@
       <url hash="bae9900f">2021.acl-tutorials.4</url>
       <doi>10.18653/v1/2021.acl-tutorials.4</doi>
       <bibkey>wang-li-2021-pre</bibkey>
+      <video href="2021.acl-tutorials.4.1.mp4"/>
+      <video href="2021.acl-tutorials.4.2.mp4"/>
+      <video href="2021.acl-tutorials.4.3.mp4"/>
     </paper>
     <paper id="5">
       <title>Prosody: Models, Methods, and Applications</title>
@@ -12765,6 +12778,29 @@
     </paper>
   </volume>
   <event id="acl-2021">
+    <meta>
+      <title>59th Annual Meeting of the Association for Computational Linguistics</title>
+      <location>Online</location>
+      <dates>August 1–6, 2021</dates>
+    </meta>
+    <links>
+      <url type="website">https://2021.aclweb.org</url>
+    </links>
+    <talk>
+      <title>Keynote 1: Advancing Technological Equity in Speech and Language Processing</title>
+      <speaker><first>Helen</first><last>Meng</last></speaker>
+      <url type="video">2021.acl.keynote1.mp4</url>
+    </talk>
+    <talk>
+      <title>Keynote 2: Learning and Processing Language from Wearables: Opportunities and Challenges</title>
+      <speaker><first>Alejandrina</first><last>Cristia</last></speaker>
+      <url type="video">2021.acl.keynote2.mp4</url>
+    </talk>
+    <talk>
+      <title>Keynote 3: Reliable Characterizations of <fixed-case>NLP</fixed-case> Systems as a Social Responsibility</title>
+      <speaker><first>Christopher</first><last>Potts</last></speaker>
+      <url type="video">2021.acl.keynote3.mp4</url>
+    </talk>
     <colocated>
       <volume-id>2021.findings-acl</volume-id>
       <volume-id>2021.bppf-1</volume-id>

data/xml/2021.emnlp.xml

@@ -14140,6 +14140,30 @@
     </paper>
   </volume>
   <event id="emnlp-2021">
+    <meta>
+      <title>The 2021 Conference on Empirical Methods in Natural Language Processing</title>
+      <location>Punta Cana, Dominican Republic</location>
+      <dates>November 7-11, 2021</dates>
+    </meta>
+    <links>
+      <url type="website">https://2021.emnlp.org</url>
+      <url type="handbook">2021.emnlp.handbook.pdf</url>
+    </links>
+    <talk>
+      <title>Keynote 1: Where next? Towards multi-text consumption via three inspired research lines</title>
+      <speaker><first>Ido</first><last>Dagan</last></speaker>
+      <url type="video">2021.emnlp.keynote1.mp4</url>
+    </talk>
+    <talk>
+      <title>Keynote 2: The language system in the human brain</title>
+      <speaker><first>Evelina</first><last>Fedorenko</last></speaker>
+      <url type="video">2021.emnlp.keynote2.mp4</url>
+    </talk>
+    <talk>
+      <title>Keynote 3: <fixed-case>LT4All</fixed-case>!? Rethinking the Agenda</title>
+      <speaker><first>Steven</first><last>Bird</last></speaker>
+      <url type="video">2021.emnlp.keynote3.mp4</url>
+    </talk>
     <colocated>
       <volume-id>2021.findings-emnlp</volume-id>
       <volume-id>2021.codi-main</volume-id>

data/xml/2021.naacl.xml

@@ -8093,6 +8093,11 @@
       <doi>10.18653/v1/2021.naacl-tutorials.5</doi>
       <bibkey>beltagy-etal-2021-beyond</bibkey>
       <pwccode url="https://github.com/allenai/naacl2021-longdoc-tutorial" additional="false">allenai/naacl2021-longdoc-tutorial</pwccode>
+      <video href="2021.naacl-tutorials.5.1.mp4"/>
+      <video href="2021.naacl-tutorials.5.2.mp4"/>
+      <video href="2021.naacl-tutorials.5.3.mp4"/>
+      <video href="2021.naacl-tutorials.5.4.mp4"/>
+      <video href="2021.naacl-tutorials.5.5.mp4"/>
     </paper>
     <paper id="6">
       <title>Crowdsourcing Natural Language Data at Scale: A Hands-On Tutorial</title>
@@ -8718,6 +8723,44 @@
     </paper>
   </volume>
   <event id="naacl-2021">
+    <meta>
+      <title>2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics</title>
+      <location>Online</location>
+      <dates>June 6-11, 2021</dates>
+    </meta>
+    <links>
+      <url type="website">https://2021.naacl.org</url>
+    </links>
+    <talk>
+      <title>Keynote 1: Humans Learn From Task Descriptions and So Should Our Models</title>
+      <speaker><first>Hinrich</first><last>Schütze</last></speaker>
+      <url type="video">2021.naacl.keynote1.mp4</url>
+    </talk>
+    <talk>
+      <title>Keynote 2: From Disembodied to Embodied Multimodal Learning</title>
+      <speaker><first>Dhruv</first><last>Batra</last></speaker>
+      <url type="video">2021.naacl.keynote2.mp4</url>
+    </talk>
+    <talk>
+      <title>Keynote 3: Generating Reality: Technical and Social Explorations in Generative Machine Learning Research</title>
+      <speaker><first>Shakir</first><last>Mohamed</last></speaker>
+      <url type="video">2021.naacl.keynote3.mp4</url>
+    </talk>
+    <talk>
+      <title>Keynote 4: Moving the Needle in <fixed-case>NLP</fixed-case> Technology for the Processing of Code-switched Language</title>
+      <speaker><first>Thamar</first><last>Solorio</last></speaker>
+      <url type="video">2021.naacl.keynote4.mp4</url>
+    </talk>
+    <talk>
+      <title>Industry Track Keynote 1: Project Debater - from grand challenge to business applications, behind the scenes and lessons learned</title>
+      <speaker><first>Aya</first><last>Soffer</last></speaker>
+      <url type="video">2021.naacl.keynote_industry1.mp4</url>
+    </talk>
+    <talk>
+      <title>Industry Track Keynote 2: <fixed-case>S</fixed-case>emantic <fixed-case>S</fixed-case>cholar - Advanced <fixed-case>NLP</fixed-case> to Accelerate Scientific Research</title>
+      <speaker><first>Dan</first><last>Weld</last></speaker>
+      <url type="video">2021.naacl.keynote_industry2.mp4</url>
+    </talk>
     <colocated>
       <volume-id>2021.alvr-1</volume-id>
       <volume-id>2021.americasnlp-1</volume-id>

data/xml/2022.acl.xml

@@ -3537,6 +3537,7 @@
       <doi>10.18653/v1/2022.acl-long.220</doi>
       <pwccode url="https://github.com/thomaslu2000/incremental-parsing-representations" additional="false">thomaslu2000/incremental-parsing-representations</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/penn-treebank">Penn Treebank</pwcdataset>
+      <video href="2022.acl-long.220.mp4"/>
     </paper>
     <paper id="221">
       <title>Knowledge Enhanced Reflection Generation for Counseling Dialogues</title>
@@ -4797,6 +4798,7 @@ in the Case of Unambiguous Gender</title>
       <revision id="1" href="2022.acl-long.298v1" hash="3dd88706"/>
       <revision id="2" href="2022.acl-long.298v2" hash="39fb17fa" date="2022-05-21">Various fixes throughout the paper.</revision>
       <doi>10.18653/v1/2022.acl-long.298</doi>
+      <video href="2022.acl-long.298.mp4"/>
     </paper>
     <paper id="299">
       <title>Improving Word Translation via Two-Stage Contrastive Learning</title>
@@ -8223,6 +8225,7 @@ in the Case of Unambiguous Gender</title>
       <bibkey>pine-etal-2022-requirements</bibkey>
       <doi>10.18653/v1/2022.acl-long.507</doi>
       <pwccode url="https://github.com/roedoejet/fastspeech2" additional="false">roedoejet/fastspeech2</pwccode>
+      <video href="2022.acl-long.507.mp4"/>
     </paper>
     <paper id="508">
       <title>Sharpness-Aware Minimization Improves Language Model Generalization</title>
@@ -12269,6 +12272,8 @@ in the Case of Unambiguous Gender</title>
       <bibkey>church-etal-2022-gentle</bibkey>
       <doi>10.18653/v1/2022.acl-tutorials.1</doi>
       <pwcdataset url="https://paperswithcode.com/dataset/glue">GLUE</pwcdataset>
+      <video href="2022.acl-tutorials.1.1.mp4"/>
+      <video href="2022.acl-tutorials.1.2.mp4"/>
     </paper>
     <paper id="2">
       <title>Towards Reproducible Machine Learning Research in Natural Language Processing</title>
@@ -12285,6 +12290,8 @@ in the Case of Unambiguous Gender</title>
       <url hash="06b2f824">2022.acl-tutorials.2</url>
       <bibkey>lucic-etal-2022-towards</bibkey>
       <doi>10.18653/v1/2022.acl-tutorials.2</doi>
+      <video href="2022.acl-tutorials.2.1.mp4"/>
+      <video href="2022.acl-tutorials.2.2.mp4"/>
     </paper>
     <paper id="3">
       <title>Knowledge-Augmented Methods for Natural Language Processing</title>
@@ -12303,6 +12310,10 @@ in the Case of Unambiguous Gender</title>
       <pwcdataset url="https://paperswithcode.com/dataset/commonsenseqa">CommonsenseQA</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conceptnet">ConceptNet</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/riddle-sense">RiddleSense</pwcdataset>
+      <video href="2022.acl-tutorials.3.1.mp4"/>
+      <video href="2022.acl-tutorials.3.2.mp4"/>
+      <video href="2022.acl-tutorials.3.3.mp4"/>
+      <video href="2022.acl-tutorials.3.4.mp4"/>
     </paper>
     <paper id="4">
       <title>Non-Autoregressive Sequence Generation</title>
@@ -12313,6 +12324,8 @@ in the Case of Unambiguous Gender</title>
       <url hash="a91a6086">2022.acl-tutorials.4</url>
       <bibkey>gu-tan-2022-non</bibkey>
       <doi>10.18653/v1/2022.acl-tutorials.4</doi>
+      <video href="2022.acl-tutorials.4.1.mp4"/>
+      <video href="2022.acl-tutorials.4.2.mp4"/>
     </paper>
     <paper id="5">
       <title>Learning with Limited Text Data</title>
@@ -12324,6 +12337,7 @@ in the Case of Unambiguous Gender</title>
       <url hash="fe4ec2d3">2022.acl-tutorials.5</url>
       <bibkey>yang-etal-2022-learning</bibkey>
       <doi>10.18653/v1/2022.acl-tutorials.5</doi>
+      <video href="2022.acl-tutorials.5.mp4"/>
     </paper>
     <paper id="6">
       <title>Zero- and Few-Shot <fixed-case>NLP</fixed-case> with Pretrained Language Models</title>
@@ -12337,6 +12351,8 @@ in the Case of Unambiguous Gender</title>
       <url hash="2e1a3511">2022.acl-tutorials.6</url>
       <bibkey>beltagy-etal-2022-zero</bibkey>
       <doi>10.18653/v1/2022.acl-tutorials.6</doi>
+      <video href="2022.acl-tutorials.6.1.mp4"/>
+      <video href="2022.acl-tutorials.6.2.mp4"/>
     </paper>
     <paper id="7">
       <title>Vision-Language Pretraining: Current Trends and the Future</title>
@@ -12349,6 +12365,9 @@ in the Case of Unambiguous Gender</title>
       <bibkey>agrawal-etal-2022-vision</bibkey>
       <doi>10.18653/v1/2022.acl-tutorials.7</doi>
       <pwcdataset url="https://paperswithcode.com/dataset/visual-question-answering">Visual Question Answering</pwcdataset>
+      <video href="2022.acl-tutorials.7.1.mp4"/>
+      <video href="2022.acl-tutorials.7.2.mp4"/>
+      <video href="2022.acl-tutorials.7.3.mp4"/>
     </paper>
     <paper id="8">
       <title>Natural Language Processing for Multilingual Task-Oriented Dialogue</title>
@@ -12362,6 +12381,8 @@ in the Case of Unambiguous Gender</title>
       <url hash="c8809ed6">2022.acl-tutorials.8</url>
       <bibkey>razumovskaia-etal-2022-natural</bibkey>
       <doi>10.18653/v1/2022.acl-tutorials.8</doi>
+      <video href="2022.acl-tutorials.8.1.mp4"/>
+      <video href="2022.acl-tutorials.8.2.mp4"/>
     </paper>
   </volume>
   <event id="acl-2022">

data/xml/2022.bea.xml

@@ -74,6 +74,7 @@
       <url hash="c462e340">2022.bea-1.4</url>
       <bibkey>chen-etal-2022-automatically</bibkey>
       <doi>10.18653/v1/2022.bea-1.4</doi>
+      <video href="2022.bea-1.4.mp4"/>
     </paper>
     <paper id="5">
       <title>A Baseline Readability Model for <fixed-case>C</fixed-case>ebuano</title>

data/xml/2022.bigscience.xml

@@ -33,6 +33,7 @@
       <url hash="b618bf84">2022.bigscience-1.1</url>
       <bibkey>jin-etal-2022-lifelong</bibkey>
       <doi>10.18653/v1/2022.bigscience-1.1</doi>
+      <video href="2022.bigscience-1.1.mp4"/>
     </paper>
     <paper id="2">
       <title>Using <fixed-case>ASR</fixed-case>-Generated Text for Spoken Language Modeling</title>

data/xml/2022.cl.xml

@@ -397,6 +397,7 @@
       <pages>849–886</pages>
       <url hash="6a8d22fb">2022.cl-4.13</url>
       <bibkey>nivre-etal-2022-nucleus</bibkey>
+      <video href="2022.cl-4.13.mp4"/>
     </paper>
     <paper id="14">
       <title>Effective Approaches to Neural Query Language Identification</title>
@@ -412,6 +413,7 @@
       <pages>887–906</pages>
       <url hash="ea9d6792">2022.cl-4.14</url>
       <bibkey>ren-etal-2022-effective</bibkey>
+      <video href="2022.cl-4.14.mp4"/>
     </paper>
     <paper id="15">
       <title>Information Theory–based Compositional Distributional Semantics</title>
@@ -424,6 +426,7 @@
       <pages>907–948</pages>
       <url hash="e6d93f6e">2022.cl-4.15</url>
       <bibkey>amigo-etal-2022-information</bibkey>
+      <video href="2022.cl-4.15.mp4"/>
     </paper>
     <paper id="16">
       <title>Revise and Resubmit: An Intertextual Model of Text-based Collaboration in Peer Review</title>
@@ -458,6 +461,7 @@
       <pages>1021–1052</pages>
       <url hash="b2d8ead8">2022.cl-4.18</url>
       <bibkey>keya-etal-2022-neural</bibkey>
+      <video href="2022.cl-4.18.mp4"/>
     </paper>
     <paper id="19">
       <title>The Text Anonymization Benchmark (<fixed-case>TAB</fixed-case>): A Dedicated Corpus and Evaluation Framework for Text Anonymization</title>
@@ -472,6 +476,7 @@
       <pages>1053–1101</pages>
       <url hash="e97fa2c7">2022.cl-4.19</url>
       <bibkey>pilan-etal-2022-text</bibkey>
+      <video href="2022.cl-4.19.mp4"/>
     </paper>
     <paper id="20">
       <title>How Much Does Lookahead Matter for Disambiguation? Partial <fixed-case>A</fixed-case>rabic Diacritization Case Study</title>
@@ -483,6 +488,7 @@
       <pages>1103–1123</pages>
       <url hash="7ca73aa5">2022.cl-4.20</url>
       <bibkey>esmail-etal-2022-much</bibkey>
+      <video href="2022.cl-4.20.mp4"/>
     </paper>
     <paper id="21">
       <title>A Metrological Perspective on Reproducibility in <fixed-case>NLP</fixed-case>*</title>