Update metadata from Papers with Code

acl-org · Nov 23, 2023 · 267e7b0 · 267e7b0
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Showing 9 changed files with 10 additions and 4 deletions.
diff --git a/data/xml/2020.aacl.xml b/data/xml/2020.aacl.xml
@@ -621,6 +621,7 @@
       <url hash="545b660a">2020.aacl-main.49</url>
       <bibkey>gao-etal-2020-systematic</bibkey>
       <pwccode url="https://github.com/HQ01/gSCAN_with_language_conditioned_embedding" additional="true">HQ01/gSCAN_with_language_conditioned_embedding</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/gscan">GSCAN</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/scan">SCAN</pwcdataset>
     </paper>
     <paper id="50">

diff --git a/data/xml/2020.emnlp.xml b/data/xml/2020.emnlp.xml
@@ -2918,7 +2918,7 @@
       <doi>10.18653/v1/2020.emnlp-main.190</doi>
       <video href="https://slideslive.com/38939080"/>
       <bibkey>sen-saffari-2020-models</bibkey>
-      <pwccode url="https://github.com/amazon-research/qa-dataset-converter" additional="false">amazon-research/qa-dataset-converter</pwccode>
+      <pwccode url="https://github.com/amazon-research/qa-dataset-converter" additional="true">amazon-research/qa-dataset-converter</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/natural-questions">Natural Questions</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/newsqa">NewsQA</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/quac">QuAC</pwcdataset>

diff --git a/data/xml/2021.emnlp.xml b/data/xml/2021.emnlp.xml
@@ -2602,6 +2602,7 @@
       <doi>10.18653/v1/2021.emnlp-main.166</doi>
       <video href="2021.emnlp-main.166.mp4"/>
       <pwccode url="https://github.com/LauraRuis/groundedSCAN" additional="true">LauraRuis/groundedSCAN</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/gscan">GSCAN</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/scan">SCAN</pwcdataset>
     </paper>
     <paper id="167">

diff --git a/data/xml/2021.findings.xml b/data/xml/2021.findings.xml
@@ -6779,6 +6779,7 @@
       <doi>10.18653/v1/2021.findings-emnlp.21</doi>
       <video href="2021.findings-emnlp.21.mp4"/>
       <pwccode url="https://github.com/ylkuo/compositional-gscan" additional="false">ylkuo/compositional-gscan</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/gscan">GSCAN</pwcdataset>
     </paper>
     <paper id="22">
       <title>An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languages</title>

diff --git a/data/xml/2022.coling.xml b/data/xml/2022.coling.xml
@@ -6891,6 +6891,7 @@
       <revision id="1" href="2022.coling-1.525v1" hash="6754108c"/>
       <revision id="2" href="2022.coling-1.525v2" hash="602a0e58" date="2023-07-31">Various corrections.</revision>
       <pwccode url="https://github.com/valvoda/neuraltransducer" additional="false">valvoda/neuraltransducer</pwccode>
+      <pwcdataset url="https://paperswithcode.com/dataset/gscan">GSCAN</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/scan">SCAN</pwcdataset>
     </paper>
     <paper id="526">

diff --git a/data/xml/2022.findings.xml b/data/xml/2022.findings.xml
@@ -2726,7 +2726,7 @@
       <bibkey>beau-crabbe-2022-impact</bibkey>
       <doi>10.18653/v1/2022.findings-acl.173</doi>
       <video href="2022.findings-acl.173.mp4"/>
-      <pwccode url="https://gitlab.com/codegenfact/BertranX" additional="false">codegenfact/BertranX</pwccode>
+      <pwccode url="https://gitlab.com/codegenfactors/BertranX" additional="true">codegenfactors/BertranX</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/conala">CoNaLa</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/django">Django</pwcdataset>
     </paper>

diff --git a/data/xml/2022.lrec.xml b/data/xml/2022.lrec.xml
@@ -768,6 +768,7 @@
       <abstract>Sentiment analysis is one of the most widely studied tasks in natural language processing. While BERT-based models have achieved state-of-the-art results in this task, little attention has been given to its performance variability across class labels, multi-source and multi-domain corpora. In this paper, we present an improved state-of-the-art and comparatively evaluate BERT-based models for sentiment analysis on Italian corpora. The proposed model is evaluated over eight sentiment analysis corpora from different domains (social media, finance, e-commerce, health, travel) and sources (Twitter, YouTube, Facebook, Amazon, Tripadvisor, Opera and Personal Healthcare Agent) on the prediction of positive, negative and neutral classes. Our findings suggest that BERT-based models are confident in predicting positive and negative examples but not as much with neutral examples. We release the sentiment analysis model as well as a newly financial domain sentiment corpus.</abstract>
       <url hash="cc707322">2022.lrec-1.62</url>
       <bibkey>roccabruna-etal-2022-multi</bibkey>
+      <pwccode url="https://gitlab.com/sislab/multi-source-multi-domain-sentiment-analysis-with-bert-based-models" additional="false">sislab/multi-source-multi-domain-sentiment-analysis-with-bert-based-models</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/imdb-movie-reviews">IMDb Movie Reviews</pwcdataset>
     </paper>
     <paper id="63">
@@ -4152,6 +4153,7 @@
       <abstract>Specialist high-quality information is typically first available in English, and it is written in a language that may be difficult to understand by most readers. While Machine Translation technologies contribute to mitigate the first issue, the translated content will most likely still contain complex language. In order to investigate and address both problems simultaneously, we introduce Simple TICO-19, a new language resource containing manual simplifications of the English and Spanish portions of the TICO-19 corpus for Machine Translation of COVID-19 literature. We provide an in-depth description of the annotation process, which entailed designing an annotation manual and employing four annotators (two native English speakers and two native Spanish speakers) who simplified over 6,000 sentences from the English and Spanish portions of the TICO-19 corpus. We report several statistics on the new dataset, focusing on analysing the improvements in readability from the original texts to their simplified versions. In addition, we propose baseline methodologies for automatically generating the simplifications, translations and joint translation and simplifications contained in our dataset.</abstract>
       <url hash="fbb6e489">2022.lrec-1.331</url>
       <bibkey>shardlow-alva-manchego-2022-simple</bibkey>
+      <pwccode url="https://github.com/mmu-tdmlab/simpletico19" additional="false">mmu-tdmlab/simpletico19</pwccode>
     </paper>
     <paper id="332">
       <title>Building Comparable Corpora for Assessing Multi-Word Term Alignment</title>

diff --git a/data/xml/N18.xml b/data/xml/N18.xml
@@ -526,7 +526,7 @@
       <doi>10.18653/v1/N18-1037</doi>
       <video href="http://vimeo.com/276453229"/>
       <bibkey>wang-etal-2018-scene</bibkey>
-      <pwccode url="https://github.com/Yusics/bist-parser" additional="false">Yusics/bist-parser</pwccode>
+      <pwccode url="https://github.com/Yusics/bist-parser" additional="true">Yusics/bist-parser</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/coco">COCO</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/visual-genome">Visual Genome</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/visual-question-answering">Visual Question Answering</pwcdataset>

diff --git a/data/xml/P19.xml b/data/xml/P19.xml
@@ -9075,7 +9075,7 @@
       <revision id="1" href="P19-1644v1" hash="590f6420"/>
       <revision id="2" href="P19-1644v2" hash="9e13eba7">In the main paper (attached), in Table 3, the row for "Cardinality (soft)" has incorrect values under the NLVR and NLVR2 columns. The respective values should be 16 and 23.6. The value of 16 was reported in Suhr et al. 2017 (P17-2034; the error occurred when I accidentally overwrote the NLVR cell value).</revision>
       <bibkey>suhr-etal-2019-corpus</bibkey>
-      <pwccode url="https://github.com/lil-lab/nlvr" additional="true">lil-lab/nlvr</pwccode>
+      <pwccode url="https://github.com/lil-lab/nlvr" additional="false">lil-lab/nlvr</pwccode>
       <pwcdataset url="https://paperswithcode.com/dataset/clevr">CLEVR</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/clevr-humans">CLEVR-Humans</pwcdataset>
       <pwcdataset url="https://paperswithcode.com/dataset/coco">COCO</pwcdataset>