Update metadata from Papers with Code

EricPeter · Aug 25, 2022 · 15e0d76 · 15e0d76
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diff --git a/data/xml/2020.repl4nlp.xml b/data/xml/2020.repl4nlp.xml
@@ -200,6 +200,13 @@
       <doi>10.18653/v1/2020.repl4nlp-1.14</doi>
       <video href="http://slideslive.com/38929780"/>
       <bibkey>lange-etal-2020-adversarial</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/basque-timebank">Basque TimeBank</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/catalan-timebank-1-0">Catalan TimeBank 1.0</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/french-timebank">French Timebank</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/krauts">KRAUTS</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/spanish-timebank-1-0">Spanish TimeBank 1.0</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/tempeval-3">TempEval-3</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/timebankpt">TimeBankPT</pwcdataset>
     </paper>
     <paper id="15">
       <title>Contextual and Non-Contextual Word Embeddings: an in-depth Linguistic Investigation</title>

diff --git a/data/xml/2021.eacl.xml b/data/xml/2021.eacl.xml
@@ -3351,6 +3351,7 @@
       <url hash="35cbca1a">2021.eacl-main.249</url>
       <bibkey>parekh-etal-2021-crisscrossed</bibkey>
       <doi>10.18653/v1/2021.eacl-main.249</doi>
+      <pwccode url="" additional="true"/>
       <pwcdataset url="https://paperswithcode.com/dataset/cxc">CxC</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/coco">COCO</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/conceptual-captions">Conceptual Captions</pwcdataset>

diff --git a/data/xml/2021.emnlp.xml b/data/xml/2021.emnlp.xml
@@ -310,7 +310,7 @@
       <bibkey>liang-etal-2021-beta</bibkey>
       <doi>10.18653/v1/2021.emnlp-main.19</doi>
       <video href="2021.emnlp-main.19.mp4"/>
-      <pwccode url="https://github.com/binliang-nlp/aagcn-acsa" additional="false">binliang-nlp/aagcn-acsa</pwccode>
+      <pwccode url="https://github.com/binliang-nlp/aagcn-acsa" additional="true">binliang-nlp/aagcn-acsa</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/conceptnet">ConceptNet</pwcdataset>
     </paper>
     <paper id="20">
@@ -540,6 +540,7 @@
       <bibkey>kung-etal-2021-efficient</bibkey>
       <doi>10.18653/v1/2021.emnlp-main.34</doi>
       <video href="2021.emnlp-main.34.mp4"/>
+      <pwccode url="https://github.com/miulab/fastmtl" additional="false">miulab/fastmtl</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/glue">GLUE</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/qnli">QNLI</pwcdataset>
     </paper>
@@ -1773,7 +1774,7 @@
       <bibkey>habernal-2021-differential</bibkey>
       <doi>10.18653/v1/2021.emnlp-main.114</doi>
       <video href="2021.emnlp-main.114.mp4"/>
-      <pwccode url="https://github.com/habernal/emnlp2021-differential-privacy-nlp" additional="false">habernal/emnlp2021-differential-privacy-nlp</pwccode>
+      <pwccode url="https://github.com/habernal/emnlp2021-differential-privacy-nlp" additional="true">habernal/emnlp2021-differential-privacy-nlp</pwccode>
     </paper>
     <paper id="115">
       <title>Achieving Model Robustness through Discrete Adversarial Training</title>

diff --git a/data/xml/2021.findings.xml b/data/xml/2021.findings.xml
@@ -11107,6 +11107,7 @@
       <url hash="337d31d9">2021.findings-emnlp.355</url>
       <bibkey>kotamraju-blanco-2021-written-justifications</bibkey>
       <doi>10.18653/v1/2021.findings-emnlp.355</doi>
+      <pwccode url="https://github.com/saketh12/forecasting_emnlp2021" additional="false">saketh12/forecasting_emnlp2021</pwccode>
     </paper>
     <paper id="356">
       <title>Cleaning Dirty Books: Post-<fixed-case>OCR</fixed-case> Processing for Previously Scanned Texts</title>

diff --git a/data/xml/2021.konvens.xml b/data/xml/2021.konvens.xml
@@ -119,6 +119,7 @@
       <pages>114–126</pages>
       <url hash="5cb3dbfc">2021.konvens-1.10</url>
       <bibkey>may-etal-2021-extraction</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/krauts">KRAUTS</pwcdataset>
     </paper>
     <paper id="11">
       <title>Automatic Phrase Recognition in Historical <fixed-case>G</fixed-case>erman</title>

diff --git a/data/xml/2022.acl.xml b/data/xml/2022.acl.xml
@@ -558,6 +558,7 @@
       <attachment type="software" hash="04007165">2022.acl-long.35.software.zip</attachment>
       <bibkey>li-xiong-2022-kafsp</bibkey>
       <doi>10.18653/v1/2022.acl-long.35</doi>
+      <pwccode url="https://github.com/tjunlp-lab/kafsp" additional="false">tjunlp-lab/kafsp</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/csqa">CSQA</pwcdataset>
     </paper>
     <paper id="36">
@@ -9679,6 +9680,7 @@ in the Case of Unambiguous Gender</title>
       <attachment type="software" hash="0d9ca22d">2022.acl-short.22.software.zip</attachment>
       <bibkey>li-etal-2022-dq</bibkey>
       <doi>10.18653/v1/2022.acl-short.22</doi>
+      <pwccode url="https://github.com/amazon-research/dq-bart" additional="false">amazon-research/dq-bart</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/cnn-daily-mail-1">CNN/Daily Mail</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/eli5">ELI5</pwcdataset>
     </paper>
@@ -11491,6 +11493,7 @@ in the Case of Unambiguous Gender</title>
       <url hash="a8b4ae72">2022.acl-demo.14</url>
       <bibkey>stodden-kallmeyer-2022-ts</bibkey>
       <doi>10.18653/v1/2022.acl-demo.14</doi>
+      <pwccode url="https://github.com/rstodden/TS_annotation_tool" additional="false">rstodden/TS_annotation_tool</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/asset">ASSET</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/asset-corpus">ASSET Corpus</pwcdataset>
     </paper>

diff --git a/data/xml/2022.findings.xml b/data/xml/2022.findings.xml
@@ -2292,6 +2292,7 @@
       <url hash="c59a5f28">2022.findings-acl.150</url>
       <bibkey>yu-etal-2022-dict</bibkey>
       <doi>10.18653/v1/2022.findings-acl.150</doi>
+      <pwccode url="https://huggingface.co/wyu1/DictBERT" additional="false">wyu1/DictBERT</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/glue">GLUE</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/qnli">QNLI</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/wnlampro">WNLaMPro</pwcdataset>
@@ -4660,6 +4661,7 @@
       <bibkey>li-etal-2022-unsupervised</bibkey>
       <doi>10.18653/v1/2022.findings-acl.310</doi>
       <pwccode url="https://github.com/liweitj47/bert_unsupervised_word_segmentation" additional="false">liweitj47/bert_unsupervised_word_segmentation</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/10000-people-human-pose-recognition-data">10,000 People - Human Pose Recognition Data</pwcdataset>
     </paper>
     <paper id="311">
       <title><fixed-case>E</fixed-case>-<fixed-case>KAR</fixed-case>: A Benchmark for Rationalizing Natural Language Analogical Reasoning</title>
@@ -5638,7 +5640,7 @@
       <url hash="769bc50a">2022.findings-naacl.47</url>
       <bibkey>nadejde-etal-2022-cocoa</bibkey>
       <doi>10.18653/v1/2022.findings-naacl.47</doi>
-      <pwccode url="https://github.com/amazon-research/contrastive-controlled-mt" additional="false">amazon-research/contrastive-controlled-mt</pwccode>
+      <pwccode url="https://github.com/awslabs/sockeye" additional="true">awslabs/sockeye</pwccode>
     </paper>
     <paper id="48">
       <title><fixed-case>CLEAR</fixed-case>: Improving Vision-Language Navigation with Cross-Lingual, Environment-Agnostic Representations</title>

diff --git a/data/xml/2022.naacl.xml b/data/xml/2022.naacl.xml
@@ -753,6 +753,7 @@
       <attachment type="software" hash="d5f65f1d">2022.naacl-main.51.software.zip</attachment>
       <bibkey>hu-etal-2022-fuse</bibkey>
       <doi>10.18653/v1/2022.naacl-main.51</doi>
+      <pwccode url="https://github.com/openvlg/della" additional="false">openvlg/della</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/penn-treebank">Penn Treebank</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/snli">SNLI</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/writingprompts">WritingPrompts</pwcdataset>
@@ -3132,7 +3133,10 @@
       <url hash="2c17196a">2022.naacl-main.210</url>
       <bibkey>ayoola-etal-2022-improving</bibkey>
       <doi>10.18653/v1/2022.naacl-main.210</doi>
+      <pwccode url="" additional="true"/>
+      <pwcdataset url="https://paperswithcode.com/dataset/ace-2004">ACE 2004</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/aida-conll-yago">AIDA CoNLL-YAGO</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/aquaint">AQUAINT</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/docred">DocRED</pwcdataset>
     </paper>
     <paper id="211">
@@ -4757,6 +4761,7 @@
       <url hash="abbd5863">2022.naacl-main.312</url>
       <bibkey>li-etal-2022-generative</bibkey>
       <doi>10.18653/v1/2022.naacl-main.312</doi>
+      <pwccode url="https://github.com/nustm/gcdda" additional="false">nustm/gcdda</pwccode>
     </paper>
     <paper id="313">
       <title><fixed-case>P</fixed-case>ro<fixed-case>QA</fixed-case>: Structural Prompt-based Pre-training for Unified Question Answering</title>
@@ -7817,8 +7822,11 @@
       <url hash="e74f6131">2022.naacl-industry.24</url>
       <bibkey>ayoola-etal-2022-refined</bibkey>
       <doi>10.18653/v1/2022.naacl-industry.24</doi>
-      <pwccode url="https://github.com/amazon-research/ReFinED" additional="false">amazon-research/ReFinED</pwccode>
+      <pwccode url="https://github.com/alexa/refined" additional="true">alexa/refined</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/ace-2004">ACE 2004</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/aida-conll-yago">AIDA CoNLL-YAGO</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/aquaint">AQUAINT</pwcdataset>
+      <pwcdataset url="https://paperswithcode.com/dataset/ipm-nel">IPM NEL</pwcdataset>
     </paper>
     <paper id="25">
       <title>Lightweight Transformers for Conversational <fixed-case>AI</fixed-case></title>

diff --git a/data/xml/D19.xml b/data/xml/D19.xml
@@ -4644,8 +4644,6 @@
       <doi>10.18653/v1/D19-1334</doi>
       <bibkey>lv-etal-2019-adapting</bibkey>
       <pwccode url="https://github.com/THU-KEG/MetaKGR" additional="false">THU-KEG/MetaKGR</pwccode>
-      <pwcdataset url="https://paperswithcode.com/dataset/fb15k">FB15k</pwcdataset>
-      <pwcdataset url="https://paperswithcode.com/dataset/fb15k-237">FB15k-237</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/nell-995">NELL-995</pwcdataset>
     </paper>
     <paper id="335">

diff --git a/data/xml/E12.xml b/data/xml/E12.xml
@@ -252,6 +252,7 @@
       <pages>266–275</pages>
       <url hash="0a077a61">E12-1027</url>
       <bibkey>costa-branco-2012-aspectual</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/timebankpt">TimeBankPT</pwcdataset>
     </paper>
     <paper id="28">
       <title>Automatic generation of short informative sentiment summaries</title>

diff --git a/data/xml/F12.xml b/data/xml/F12.xml
@@ -1415,6 +1415,7 @@
       <pages>463–470</pages>
       <url hash="35005673">F12-2041</url>
       <bibkey>bittar-hagege-2012-un</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/french-timebank">French Timebank</pwcdataset>
     </paper>
     <paper id="42">
       <title>Vers le <fixed-case>FDTB</fixed-case> : <fixed-case>F</fixed-case>rench Discourse Tree Bank (Towards the <fixed-case>FDTB</fixed-case> : <fixed-case>F</fixed-case>rench Discourse Tree Bank) [in <fixed-case>F</fixed-case>rench]</title>

diff --git a/data/xml/F14.xml b/data/xml/F14.xml
@@ -585,6 +585,7 @@
       <pages>562-567</pages>
       <url hash="9209429f">F14-2029</url>
       <bibkey>lefeuvre-etal-2014-tense</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/french-timebank">French Timebank</pwcdataset>
     </paper>
     <paper id="30">
       <title>Automatic identification of document sections for designing a <fixed-case>F</fixed-case>rench clinical corpus (Identification automatique de zones dans des documents pour la constitution d’un corpus médical en français) [in <fixed-case>F</fixed-case>rench]</title>

diff --git a/data/xml/L18.xml b/data/xml/L18.xml
@@ -805,6 +805,7 @@
       <url hash="94491fbb">L18-1085</url>
       <bibkey>strotgen-etal-2018-krauts</bibkey>
       <pwccode url="https://github.com/JannikStroetgen/KRAUTS" additional="false">JannikStroetgen/KRAUTS</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/krauts">KRAUTS</pwcdataset>
     </paper>
     <paper id="86">
       <title><fixed-case>C</fixed-case>og<fixed-case>C</fixed-case>omp<fixed-case>NLP</fixed-case>: Your <fixed-case>S</fixed-case>wiss Army Knife for <fixed-case>NLP</fixed-case></title>

diff --git a/data/xml/N18.xml b/data/xml/N18.xml
@@ -3458,7 +3458,6 @@
       <doi>10.18653/v1/N18-2053</doi>
       <bibkey>nguyen-etal-2018-novel</bibkey>
       <pwccode url="https://github.com/daiquocnguyen/ConvKB" additional="true">daiquocnguyen/ConvKB</pwccode>
-      <pwcdataset url="https://paperswithcode.com/dataset/fb15k">FB15k</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/fb15k-237">FB15k-237</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/wn18">WN18</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/wn18rr">WN18RR</pwcdataset>

diff --git a/data/xml/N19.xml b/data/xml/N19.xml
@@ -3052,7 +3052,6 @@
       <doi>10.18653/v1/N19-1226</doi>
       <bibkey>nguyen-etal-2019-capsule</bibkey>
       <pwccode url="https://github.com/daiquocnguyen/CapsE" additional="true">daiquocnguyen/CapsE</pwccode>
-      <pwcdataset url="https://paperswithcode.com/dataset/fb15k">FB15k</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/fb15k-237">FB15k-237</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/wn18">WN18</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/wn18rr">WN18RR</pwcdataset>

diff --git a/data/xml/W13.xml b/data/xml/W13.xml
@@ -72,6 +72,7 @@
       <pages>59–70</pages>
       <url hash="1139abfd">W13-0106</url>
       <bibkey>costa-branco-2013-temporal</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/timebankpt">TimeBankPT</pwcdataset>
     </paper>
     <paper id="7">
       <title>Empirical Validation of Reichenbach’s Tense Framework</title>

diff --git a/data/xml/W17.xml b/data/xml/W17.xml
@@ -13535,6 +13535,7 @@ with emotion annotation. We (a) analyse annotation reliability and annotation me
       <author><first>Fabienne</first><last>Martin</last></author>
       <url hash="5b61023f">W17-6807</url>
       <bibkey>falk-martin-2017-towards-inferential</bibkey>
+      <pwcdataset url="https://paperswithcode.com/dataset/french-timebank">French Timebank</pwcdataset>
     </paper>
     <paper id="8">
       <title>Learning to Compose Spatial Relations with Grounded Neural Language Models</title>