Update metadata from Papers with Code

data/xml/2016.iwslt.xml

@@ -96,6 +96,7 @@
       <url hash="30f93f67">2016.iwslt-1.8</url>
       <bibkey>lazaridis-etal-2016-investigating</bibkey>
       <pwcdataset url="https://paperswithcode.com/dataset/librispeech">LibriSpeech</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/ted-lium-3">TED-LIUM</pwcdataset>
     </paper>
     <paper id="9">
       <title>Towards Improving Low-Resource Speech Recognition Using Articulatory and Language Features</title>

data/xml/2018.iwslt.xml

@@ -167,6 +167,7 @@
       <abstract>This paper describes the MeMAD project entry to the IWSLT Speech Translation Shared Task, addressing the translation of English audio into German text. Between the pipeline and end-to-end model tracks, we participated only in the former, with three contrastive systems. We tried also the latter, but were not able to finish our end-to-end model in time. All of our systems start by transcribing the audio into text through an automatic speech recognition (ASR) model trained on the TED-LIUM English Speech Recognition Corpus (TED-LIUM). Afterwards, we feed the transcripts into English-German text-based neural machine translation (NMT) models. Our systems employ three different translation models trained on separate training sets compiled from the English-German part of the TED Speech Translation Corpus (TED-TRANS) and the OPENSUBTITLES2018 section of the OPUS collection. In this paper, we also describe the experiments leading up to our final systems. Our experiments indicate that using OPENSUBTITLES2018 in training significantly improves translation performance. We also experimented with various preand postprocessing routines for the NMT module, but we did not have much success with these. Our best-scoring system attains a BLEU score of 16.45 on the test set for this year’s task.</abstract>
       <url hash="9b99e769">2018.iwslt-1.13</url>
       <bibkey>sulubacak-etal-2018-memad</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/ted-lium-3">TED-LIUM</pwcdataset>
     </paper>
     <paper id="14">
       <title>Prompsit’s Submission to the <fixed-case>IWSLT</fixed-case> 2018 Low Resource Machine Translation Task</title>

data/xml/2019.iwslt.xml

@@ -74,6 +74,7 @@
       <bibkey>inaguma-etal-2019-espnet</bibkey>
       <pwcdataset url="https://paperswithcode.com/dataset/librispeech">LibriSpeech</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/must-c">MuST-C</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/ted-lium-3">TED-LIUM</pwcdataset>
     </paper>
     <paper id="5">
       <title><fixed-case>ON</fixed-case>-<fixed-case>TRAC</fixed-case> Consortium End-to-End Speech Translation Systems for the <fixed-case>IWSLT</fixed-case> 2019 Shared Task</title>
@@ -82,7 +83,6 @@
       <url hash="4b4966fb">2019.iwslt-1.5</url>
       <bibkey>nguyen-2019-trac</bibkey>
       <pwcdataset url="https://paperswithcode.com/dataset/must-c">MuST-C</pwcdataset>
-      <pwcdataset url="https://paperswithcode.com/dataset/ted-lium-3">TED-LIUM 3</pwcdataset>
     </paper>
     <paper id="6">
       <title>Transformer-based Cascaded Multimodal Speech Translation</title>

data/xml/2020.acl.xml

@@ -673,6 +673,7 @@
       <video href="http://slideslive.com/38928694"/>
       <bibkey>li-etal-2020-dice</bibkey>
       <pwccode url="https://github.com/ShannonAI/dice_loss_for_NLP" additional="true">ShannonAI/dice_loss_for_NLP</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/msra-cn-ner">MSRA CN NER</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ontonotes-4-0">OntoNotes 4.0</pwcdataset>
@@ -2819,6 +2820,7 @@
       <video href="http://slideslive.com/38928920"/>
       <bibkey>jiang-etal-2020-generalizing</bibkey>
       <pwccode url="https://github.com/jzbjyb/SpanRel" additional="true">jzbjyb/SpanRel</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2012-1">CoNLL-2012</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/oie2016">OIE2016</pwcdataset>
@@ -4469,6 +4471,7 @@
       <video href="http://slideslive.com/38928756"/>
       <bibkey>zhang-etal-2020-efficient</bibkey>
       <pwccode url="https://github.com/yzhangcs/crfpar" additional="true">yzhangcs/crfpar</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2009">CoNLL-2009</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/penn-treebank">Penn Treebank</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/universal-dependencies">Universal Dependencies</pwcdataset>
@@ -5764,6 +5767,7 @@
       <video href="http://slideslive.com/38929265"/>
       <bibkey>kaneko-etal-2020-encoder</bibkey>
       <pwccode url="https://github.com/kanekomasahiro/bert-gec" additional="false">kanekomasahiro/bert-gec</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2014-shared-task-grammatical-error">CoNLL-2014 Shared Task: Grammatical Error Correction</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/jfleg">JFLEG</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/locness-corpus">WI-LOCNESS</pwcdataset>
@@ -7705,6 +7709,7 @@
       <pwccode url="https://github.com/ShannonAI/mrc-for-flat-nested-ner" additional="true">ShannonAI/mrc-for-flat-nested-ner</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2004">ACE 2004</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2005">ACE 2005</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/genia">GENIA</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/msra-cn-ner">MSRA CN NER</pwcdataset>
@@ -8575,6 +8580,7 @@
       <pwccode url="https://github.com/juntaoy/biaffine-ner" additional="false">juntaoy/biaffine-ner</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2004">ACE 2004</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2005">ACE 2005</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2002">CoNLL 2002</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/genia">GENIA</pwcdataset>
@@ -8637,6 +8643,7 @@
       <video href="http://slideslive.com/38929366"/>
       <bibkey>wu-etal-2020-single</bibkey>
       <pwccode url="https://github.com/microsoft/vert-papers/tree/master/papers/SingleMulti-TS" additional="false">microsoft/vert-papers</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2002">CoNLL 2002</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
     </paper>
@@ -9263,6 +9270,7 @@
       <video href="http://slideslive.com/38928701"/>
       <bibkey>wu-etal-2020-corefqa</bibkey>
       <pwccode url="https://github.com/ShannonAI/CorefQA" additional="false">ShannonAI/CorefQA</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2012-1">CoNLL-2012</pwcdataset>
     </paper>
     <paper id="623">
@@ -11523,6 +11531,7 @@
       <doi>10.18653/v1/2020.acl-main.777</doi>
       <video href="http://slideslive.com/38929132"/>
       <bibkey>chen-etal-2020-seqvat</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2000-1">CoNLL-2000</pwcdataset>
     </paper>
     <paper id="778">

data/xml/2020.bea.xml

@@ -222,6 +222,7 @@
       <doi>10.18653/v1/2020.bea-1.16</doi>
       <bibkey>omelianchuk-etal-2020-gector</bibkey>
       <pwccode url="https://github.com/grammarly/gector" additional="true">grammarly/gector</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2014-shared-task-grammatical-error">CoNLL-2014 Shared Task: Grammatical Error Correction</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/fce">FCE</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/locness-corpus">WI-LOCNESS</pwcdataset>

data/xml/2020.coling.xml

@@ -1051,6 +1051,7 @@
       <doi>10.18653/v1/2020.coling-main.78</doi>
       <bibkey>luoma-pyysalo-2020-exploring</bibkey>
       <pwccode url="https://github.com/jouniluoma/bert-ner-cmv" additional="false">jouniluoma/bert-ner-cmv</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2002">CoNLL 2002</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
     </paper>

data/xml/2020.emnlp.xml

@@ -2042,6 +2042,7 @@
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2004">ACE 2004</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2005">ACE 2005</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ade-corpus">Adverse Drug Events (ADE) Corpus</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll04">CoNLL04</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/fewrel">FewRel</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/wiki-zsl">Wiki-ZSL</pwcdataset>
@@ -7329,6 +7330,7 @@
       <bibkey>wang-etal-2020-ain</bibkey>
       <pwccode url="https://github.com/Alibaba-NLP/AIN" additional="false">Alibaba-NLP/AIN</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/atis">ATIS</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
     </paper>
     <paper id="486">
@@ -7903,6 +7905,7 @@
       <video href="https://slideslive.com/38938803"/>
       <bibkey>yamada-etal-2020-luke</bibkey>
       <pwccode url="https://github.com/studio-ousia/luke" additional="true">studio-ousia/luke</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/open-entity-1">Open Entity</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/record">ReCoRD</pwcdataset>
@@ -10400,6 +10403,7 @@
       <video href="https://slideslive.com/38938926"/>
       <bibkey>toshniwal-etal-2020-learning</bibkey>
       <pwccode url="https://github.com/shtoshni92/long-doc-coref" additional="true">shtoshni92/long-doc-coref</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2012-1">CoNLL-2012</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ontonotes-5-0">OntoNotes 5.0</pwcdataset>
     </paper>
@@ -10414,6 +10418,7 @@
       <video href="https://slideslive.com/38938952"/>
       <bibkey>xu-choi-2020-revealing</bibkey>
       <pwccode url="https://github.com/lxucs/coref-hoi" additional="false">lxucs/coref-hoi</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2012-1">CoNLL-2012</pwcdataset>
     </paper>
     <paper id="687">

data/xml/2020.findings.xml

@@ -417,6 +417,7 @@
       <doi>10.18653/v1/2020.findings-emnlp.28</doi>
       <video href="https://slideslive.com/38940127"/>
       <bibkey>chen-etal-2020-enhance</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2000-1">CoNLL-2000</pwcdataset>
     </paper>
@@ -4408,6 +4409,7 @@
       <video href="https://slideslive.com/38940634"/>
       <bibkey>szymanski-etal-2020-wer</bibkey>
       <pwcdataset url="https://paperswithcode.com/dataset/librispeech">LibriSpeech</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/ted-lium-3">TED-LIUM</pwcdataset>
     </paper>
     <paper id="296">
       <title>Detecting Stance in Media On Global Warming</title>
@@ -5278,6 +5280,7 @@
       <url hash="42f6e4b0">2020.findings-emnlp.356</url>
       <doi>10.18653/v1/2020.findings-emnlp.356</doi>
       <bibkey>wang-etal-2020-embeddings</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
     </paper>
     <paper id="357">

data/xml/2020.iwslt.xml

@@ -75,7 +75,6 @@
       <bibkey>elbayad-etal-2020-trac</bibkey>
       <pwcdataset url="https://paperswithcode.com/dataset/how2">How2</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/must-c">MuST-C</pwcdataset>
-      <pwcdataset url="https://paperswithcode.com/dataset/ted-lium-3">TED-LIUM 3</pwcdataset>
     </paper>
     <paper id="3">
       <title>Start-Before-End and End-to-End: Neural Speech Translation by <fixed-case>A</fixed-case>pp<fixed-case>T</fixed-case>ek and <fixed-case>RWTH</fixed-case> <fixed-case>A</fixed-case>achen <fixed-case>U</fixed-case>niversity</title>
@@ -393,6 +392,7 @@
       <doi>10.18653/v1/2020.iwslt-1.25</doi>
       <video href="http://slideslive.com/38929595"/>
       <bibkey>machacek-etal-2020-elitr</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/ted-lium-3">TED-LIUM</pwcdataset>
     </paper>
     <paper id="26">
       <title>Is 42 the Answer to Everything in Subtitling-oriented Speech Translation?</title>

data/xml/2020.lrec.xml

@@ -52,6 +52,7 @@
       <language>eng</language>
       <bibkey>yu-etal-2020-cluster</bibkey>
       <pwccode url="https://github.com/juntaoy/dali-full-anaphora" additional="false">juntaoy/dali-full-anaphora</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2012-1">CoNLL-2012</pwcdataset>
     </paper>
     <paper id="3">

data/xml/2020.repl4nlp.xml

@@ -33,6 +33,7 @@
       <doi>10.18653/v1/2020.repl4nlp-1.1</doi>
       <video href="http://slideslive.com/38929767"/>
       <bibkey>liu-etal-2020-zero</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll04">CoNLL04</pwcdataset>
     </paper>
     <paper id="2">

data/xml/2021.acl.xml

@@ -2301,6 +2301,7 @@
       <pwccode url="https://github.com/modelscope/adaseq" additional="true">modelscope/adaseq</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/bc5cdr">BC5CDR</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/cmeee">CMeEE</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll">CoNLL++</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2000-1">CoNLL-2000</pwcdataset>
@@ -3366,6 +3367,7 @@
       <bibkey>wang-etal-2021-automated</bibkey>
       <video href="2021.acl-long.206.mp4"/>
       <pwccode url="https://github.com/Alibaba-NLP/ACE" additional="true">Alibaba-NLP/ACE</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2002">CoNLL 2002</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2000-1">CoNLL-2000</pwcdataset>
@@ -3527,6 +3529,7 @@
       <pwccode url="https://github.com/tricktreat/locate-and-label" additional="false">tricktreat/locate-and-label</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2004">ACE 2004</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2005">ACE 2005</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/genia">GENIA</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/weibo-ner">Weibo NER</pwcdataset>
@@ -7340,6 +7343,7 @@
       <pwccode url="https://github.com/yhcc/BARTNER" additional="false">yhcc/BARTNER</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2004">ACE 2004</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ace-2005">ACE 2005</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2003">CoNLL 2003</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/genia">GENIA</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/ontonotes-5-0">OntoNotes 5.0</pwcdataset>
@@ -8330,6 +8334,7 @@
       <doi>10.18653/v1/2021.acl-long.511</doi>
       <bibkey>colombo-etal-2021-novel</bibkey>
       <video href="2021.acl-long.511.mp4"/>
+      <pwcdataset url="https://paperswithcode.com/dataset/yelp">Yelp</pwcdataset>
     </paper>
     <paper id="512">
       <title>Determinantal Beam Search</title>
@@ -9368,6 +9373,7 @@
       <bibkey>kirstain-etal-2021-coreference</bibkey>
       <video href="2021.acl-short.3.mp4"/>
       <pwccode url="https://github.com/yuvalkirstain/s2e-coref" additional="false">yuvalkirstain/s2e-coref</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2012-1">CoNLL-2012</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/gap-coreference-dataset">GAP Coreference Dataset</pwcdataset>
     </paper>
@@ -10628,6 +10634,7 @@
       <pwccode url="https://github.com/google-research-datasets/clang8" additional="true">google-research-datasets/clang8</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/akces-gec">AKCES-GEC</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/c4">C4</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conll-2014-shared-task-grammatical-error">CoNLL-2014 Shared Task: Grammatical Error Correction</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/fce">FCE</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/mc4">mC4</pwcdataset>

data/xml/2021.eacl.xml

@@ -584,6 +584,7 @@
       <doi>10.18653/v1/2021.eacl-main.40</doi>
       <pwccode url="https://github.com/ManojPrabhakar/CHOLAN" additional="false">ManojPrabhakar/CHOLAN</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/aida-conll-yago">AIDA CoNLL-YAGO</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/conll-1">CoNLL</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/dbpedia">DBpedia</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/t-rex">T-REx</pwcdataset>
     </paper>