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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<meta name="description" content="Information about XGLUE Dataset">
<meta name="author" content="Daniel Campos">
<title>XGLUE</title>
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clicked = true;
}
alert("Download Links are now viewable")
} else {
alert("Please Agree to our conditions to download the dataset")
}
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<style>
code {
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<nav class="navbar navbar-expand-lg navbar-dark fixed-top topnav" id="mainNav">
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<a class="nav-link js-scroll-trigger" href="#intro">Intro</a>
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<a class="nav-link js-scroll-trigger" href="#leaderboard">Leaderboard</a>
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<a class="nav-link js-scroll-trigger" href="#contact">Contact</a>
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<section id="intro">
<div class="container">
<center>
<img src="img/MicrosoftLogo.png">
</center>
<div class="row">
<p>XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained models with respect to cross-lingual natural language understanding and generation. </p>
<p><b>For people who are working on XTREME, we recommend you to submit results to XGLUE as well, especially for the XGLUE unique tasks, as (1) XGLUE includes tasks (News Classification, Query-Ad Matching, Web Page Ranking and QA Matching) from real-world scenarios, and all these datasets are generated and labeled by human, instead of MT engines; (2) XGLUE provides two cross-lingual text generation tasks.</b></p>
<p>XGLUE is composed of 11 tasks spans 19 languages. For each task, the training data is only available in English. This means that to succeed at XGLUE, a model must have a strong zero-shot cross-lingual transfer capability to learn from the English data of a specific task and transfer what it learned to other languages. Comparing to its concurrent work XTREME, XGLUE has two characteristics: First, it includes cross-lingual NLU and cross-lingual NLG tasks at the same time; Second, besides including 5 existing cross-lingual tasks (i.e. NER, POS, MLQA, PAWS-X and XNLI), XGLUE selects 6 new tasks from Bing scenarios as well, including News Classification (NC), Query-Ad Matching (QADSM), Web Page Ranking (WPR), QA Matching (QAM), Question Generation (QG) and News Title Generation (NTG). Such diversities of languages, tasks and task origin provide a comprehensive benchmark for quantifying the quality of a pre-trained model on cross-lingual natural language understanding and generation.</p>
</div>
<div class="row">
<h3>Important Updates</h3>
</div>
<div class="row">
<ul>
<li>2021-04-28: add sub-scores for XGLUE unique tasks.</li>
<li>2020-11-26: release label of test dataset.</li>
<li>2020-09-14: add two sub-scores "XGLUE-Understanding Score" and "XGLUE-Generation Score".</li>
</ul>
<p></p>
</div>
<div class="row">
<h3>Terms and Conditions</h3>
<p>The XGLUE datasets are intended for non-commercial research purposes only to promote advancement in the field of artificial intelligence and related areas, and is made available free of charge without extending any license or other intellectual property rights. The dataset is provided “as is” without warranty and usage of the data has risks since we may not own the underlying rights in the documents. We are not be liable for any damages related to use of the dataset. Feedback is voluntarily given and can be used as we see fit. Upon violation of any of these terms, your rights to use the dataset will end automatically.</p><br /><br /> <p> If you have questions about use of the dataset or any research outputs in your products or services, we encourage you to undertake your own independent legal review. For other questions, please feel free to contact us.</p>
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I agree to terms and conditions. Upon accepting links to dataset will become available.
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<button type="button" class="btn btn-primary btn-default" onclick='return addDownloadLink()'>Submit</button>
</div>
</div>
</section>
<section id="leaderboard" class="bg-light">
<div class="container">
<div class="row">
<div class="table-responsive">
<h2>XGLUE Dataset and Leaderboard</h2>
<h4>Tasks</h4>
<ol>
<li>NER</li>
<li>POS Tagging (POS)</li>
<li>News Classification (NC)</li>
<li>MLQA</li>
<li>XNLI</li>
<li>PAWS-X</li>
<li>Query-Ad Matching (QADSM)</li>
<li>Web Page Ranking (WPR)</li>
<li>QA Matching (QAM)</li>
<li>Question Generation (QG)</li>
<li>News Title Generation (NTG)</li>
</ol>
<h4>Relevant Links</h4>
<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://github.com/microsoft/XGLUE">XGLUE Submission Guideline/Github</a>
<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://arxiv.org/abs/2004.01401">XGLUE Paper</a>
<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://github.com/microsoft/Unicoder">Unicoder Baseline</a>
<div class="row"> </div>
<div id="xgluedata"> </div>
<div class="row"> </div>
<h4>Understanding Leaderboard ranked by XGLUE Understanding Score (Average on task 1-9)</h4>
<h5> </h5>
<div style="text-align:center">
<table class="table table-striped" id='xgluetable' style="font-size:80%">
<thead>
<tr>
<th>Rank</th>
<th class="col-md-9">Model</th>
<th class="col-md-1">Submission Date</th>
<th class="col-md-12">Dataset Translation</th>
<th class="param">Parameter (Million)</th>
<th class="col-md-1">NER</th>
<th class="col-md-1">POS</th>
<th class="col-md-1">NC</th>
<th class="col-md-1">MLQA</th>
<th class="col-md-1">XNLI</th>
<th class="col-md-1">PAWS-X</th>
<th class="col-md-1">QADSM</th>
<th class="col-md-1">WPR</th>
<th class="col-md-1">QAM</th>
<th class="col-md-1">XGLUE-Understanding Score</th>
</tr>
</thead>
<tbody>
<tbody>
<tr>
<td><strong><a href="https://arxiv.org/abs/2009.05166">FILTER</a></strong><br/> (Microsoft Dynamics 365 AI Research)</td>
<td>2020-09-14</a></td>
<td>Yes</td>
<td>550M</td>
<td>82.6</td>
<td>81.6</td>
<td>83.5</td>
<td>76.2</td>
<td>83.9</td>
<td>93.8</td>
<td>71.4</td>
<td>74.7</td>
<td>73.4</td>
<td>80.1</td>
</tr>
<tr>
<td><strong>Unicoder Baseline</strong><br/> (XGLUE Team)</td>
<td>2020-05-25</a></td>
<td>No</td>
<td>270M</td>
<td>79.7</td>
<td>79.6</td>
<td>83.5</td>
<td>66.0</td>
<td>75.3</td>
<td>90.1</td>
<td>68.4</td>
<td>73.9</td>
<td>68.9</td>
<td>76.1</td>
</tr>
</tbody>
</table>
</div>
<div class="row"> </div>
<h4>Understanding Leaderboard ranked by XGLUE Unique Task Score (Average on task 3,7,8,9)</h4>
<h5> </h5>
<div style="text-align:center">
<table class="table table-striped" id='xgluetable3' style="font-size:80%;width:75%">
<thead>
<tr>
<th>Rank</th>
<th class="col-md-9">Model</th>
<th class="col-md-1">Submission Date</th>
<th class="col-md-12">Dataset Translation</th>
<th class="param">Parameter (Million)</th>
<th class="col-md-1">NC</th>
<th class="col-md-1">QADSM</th>
<th class="col-md-1">WPR</th>
<th class="col-md-1">QAM</th>
<th class="col-md-1">XGLUE Unique Score</th>
</tr>
</thead>
<tbody>
<tbody>
<tr>
<td><strong><a href="https://arxiv.org/abs/2009.05166">FILTER</a></strong><br/> (Microsoft Dynamics 365 AI Research)</td>
<td>2020-09-14</a></td>
<td>Yes</td>
<td>550M</td>
<td>83.5</td>
<td>71.4</td>
<td>74.7</td>
<td>73.4</td>
<td>75.8</td>
</tr>
<tr>
<td><strong>Unicoder Baseline</strong><br/> (XGLUE Team)</td>
<td>2020-05-25</a></td>
<td>No</td>
<td>270M</td>
<td>83.5</td>
<td>68.4</td>
<td>73.9</td>
<td>68.9</td>
<td>73.7</td>
</tr>
</tbody>
</table>
</div>
<h4>Generation Leaderboard ranked by XGLUE Generation Score (Average on task 10, 11)</h4>
<div style="text-align:center">
<table class="table table-striped" id='xgluetable2' style="font-size:80%;width:70%">
<thead>
<tr>
<th>Rank</th>
<th class="col-md-1">Model</th>
<th class="col-md-1">Submission Date</th>
<th class="col-md-12">Dataset Translation</th>
<th class="param">Parameter (Million)</th>
<th class="col-md-1">QG</th>
<th class="col-md-1">NTG</th>
<th class="col-md-1">XGLUE-Generation Score</th>
</tr>
</thead>
<tbody>
<tbody>
<tr>
<td><strong>SAG</strong><br/> (MS Ads Creative)</td>
<td>2022-01-12</td>
<td>Yes</td>
<td>270M</td>
<td>12.6</td>
<td>12.4</td>
<td>12.5</td>
</tr>
<tr>
<td><strong><a href="https://arxiv.org/abs/2104.08006">ProphetNet-X</a></strong><br/> (USTC+MSRA)</td>
<td>2021-04-22</td>
<td>No</td>
<td>270M</td>
<td>12.2</td>
<td>11.6</td>
<td>11.9</td>
</tr>
<tr>
<td><strong>Unicoder Baseline</strong><br/> (XGLUE Team)</td>
<td>2020-05-25</td>
<td>No</td>
<td>270M</td>
<td>10.6</td>
<td>10.7</td>
<td>10.7</td>
</tr>
<tr>
<td><strong>MP-Tune</strong><br/> (ByteDance MLNLC)</td>
<td>2021-01-12</td>
<td>Yes</td>
<td>304M</td>
<td>8.1</td>
<td>9.4</td>
<td>8.7</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
</section>
<section id="contact" class="bg-light">
<div class="container">
<div class="row">
<div class="col-md-12 mx-auto">
<h1>XGLUE Submission Instructions</h1>
<p>Once you have built a model that meets your expectations on evaluation with the dev set, you can submit your test results to get official evaluation on the test set. To ensure the integrity of the official test results, we do not release the correct answers for test set to the public. To submit your model for official evaluation on the test set, follow the below steps:</p>
<ol>
<li>Generate your prediction output for the dev set.</li>
<li>Run the official evaluation methodologies found in the task specific git repo and verify your systems are running as expected.</li>
<li>Generate your prediction output for the test set and submit the following information by <script type="text/javascript">gen_mail_to_link('xglue','microsoft.com','XGLUE Submission','emailing us');</script>.</li>
</ol>
<p>Your email should include:</p>
<ol>
<li>Prediction results on test set. [Required]</li>
<li>Prediction results on dev set. [Recommended]</li>
<li>Individual/Team Name: Name of the individual or the team to appear in the leaderboard. [Required]</li>
<li>Individual/Team Institution: Name of the institution of the individual or the team to appear in the leaderboard. [Optional]</li>
<li>Model code: Training code for the model. [Recommended]</li>
<li>Model information: Name of the model/technique to appear in the leaderboard, whether used translated data in fine-tuning, the parameter number of model. [Required]</li>
<li>Paper Information: Name, Citation, URL of the paper if model is from a published work to appear in the leaderboard. [Optional]</li>
</ol>
<p>To avoid "P-hacking" we discourage too many submissions from the same group in a short period of time.</p>
</div>
</div>
</div>
</section>
<section id="about" class="bg-light">
<div class="container">
<div class="row">
<div class="col-md-12 mx-auto">
<h1>About XGLUE</h1>
<h3></h3>
<div class="row">
<div class="col-md-12"><p>XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained models with respect to cross-lingual natural language understanding and generation.</p></div>
</div>
<h2>How to cite</h2>
<div style="overflow-x:scroll; white-space: nowrap">
<code>@article{Liang2020XGLUEAN,<br>
title={XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation},<br>
author={Yaobo Liang and Nan Duan and Yeyun Gong and Ning Wu and Fenfei Guo and Weizhen Qi and Ming Gong and Linjun Shou and Daxin Jiang and Guihong Cao and Xiaodong Fan and Ruofei Zhang and Rahul Agrawal and Edward Cui and Sining Wei and Taroon Bharti and Ying Qiao and Jiun-Hung Chen and Winnie Wu and Shuguang Liu and Fan Yang and Daniel Campos and Rangan Majumder and Ming Zhou},<br>
journal={arXiv},<br>
year={2020},<br>
volume={abs/2004.01401}<br>
}</code>
</div>
<p></p>
<p>Additionally, since XGLUE is also built out of exiting 5 datasets, please ensure you cite all of them.</p>
<p>An example: We evaluate our model using the XGLUE benchmark \cite{Liang2020XGLUEAN}, a cross-lingual evaluation benchmark consiting of Named Entity Resolution (NER) \cite{Sang2002IntroductionTT} \cite{Sang2003IntroductionTT}, Part of Speech Tagging (POS) \cite{11234/1-3105}, News Classification (NC), MLQA \cite{Lewis2019MLQAEC}, XNLI \cite{Conneau2018XNLIEC}, PAWS-X \cite{Yang2019PAWSXAC}, Query-Ad Matching (QADSM), Web Page Ranking (WPR), QA Matching (QAM), Question Generation (QG) and News Title Generation (NTG).</p>
<div style="overflow-x:scroll; white-space: nowrap">
<code>@misc{11234/1-3105,<br>
title={Universal Dependencies 2.5},<br>
author={Zeman, Daniel and Nivre, Joakim and Abrams, Mitchell and Aepli, No{\"e}mi and Agi{\'c}, {\v Z}eljko and Ahrenberg, Lars and Aleksandravi{\v c}i{\=u}t{\.e}, Gabriel{\.e} and Antonsen, Lene and Aplonova, Katya and Aranzabe, Maria Jesus and Arutie, Gashaw and Asahara, Masayuki and Ateyah, Luma and Attia, Mohammed and Atutxa, Aitziber and Augustinus, Liesbeth and Badmaeva, Elena and Ballesteros, Miguel and Banerjee, Esha and Bank, Sebastian and Barbu Mititelu, Verginica and Basmov, Victoria and Batchelor, Colin and Bauer, John and Bellato, Sandra and Bengoetxea, Kepa and Berzak, Yevgeni and Bhat, Irshad Ahmad and Bhat, Riyaz Ahmad and Biagetti, Erica and Bick, Eckhard and Bielinskien{\.e}, Agn{\.e} and Blokland, Rogier and Bobicev, Victoria and Boizou, Lo{\"{\i}}c and Borges V{\"o}lker, Emanuel and B{\"o}rstell, Carl and Bosco, Cristina and Bouma, Gosse and Bowman, Sam and Boyd, Adriane and Brokait{\.e}, Kristina and Burchardt, Aljoscha and Candito, Marie and Caron, Bernard and Caron, Gauthier and Cavalcanti, Tatiana and Cebiro{\u g}lu Eryi{\u g}it, G{\"u}l{\c s}en and Cecchini, Flavio Massimiliano and Celano, Giuseppe G. A. and {\v C}{\'e}pl{\"o}, Slavom{\'{\i}}r and Cetin, Savas and Chalub, Fabricio and Choi, Jinho and Cho, Yongseok and Chun, Jayeol and Cignarella, Alessandra T. and Cinkov{\'a}, Silvie and Collomb, Aur{\'e}lie and {\c C}{\"o}ltekin, {\c C}a{\u g}r{\i} and Connor, Miriam and Courtin, Marine and Davidson, Elizabeth and de Marneffe, Marie-Catherine and de Paiva, Valeria and de Souza, Elvis and Diaz de Ilarraza, Arantza and Dickerson, Carly and Dione, Bamba and Dirix, Peter and Dobrovoljc, Kaja and Dozat, Timothy and Droganova, Kira and Dwivedi, Puneet and Eckhoff, Hanne and Eli, Marhaba and Elkahky, Ali and Ephrem, Binyam and Erina, Olga and Erjavec, Toma{\v z} and Etienne, Aline and Evelyn, Wograine and Farkas, Rich{\'a}rd and Fernandez Alcalde, Hector and Foster, Jennifer and Freitas, Cl{\'a}udia and Fujita, Kazunori and Gajdo{\v s}ov{\'a}, Katar{\'{\i}}na and Galbraith, Daniel and Garcia, Marcos and G{\"a}rdenfors, Moa and Garza, Sebastian and Gerdes, Kim and Ginter, Filip and Goenaga, Iakes and Gojenola, Koldo and G{\"o}k{\i}rmak, Memduh and Goldberg, Yoav and G{\'o}mez Guinovart, Xavier and Gonz{\'a}lez Saavedra, Berta and Grici{\=u}t{\.e}, Bernadeta and Grioni, Matias and Gr{\=u}z{\={\i}}tis, Normunds and Guillaume, Bruno and Guillot-Barbance, C{\'e}line and Habash, Nizar and Haji{\v c}, Jan and Haji{\v c} jr., Jan and H{\"a}m{\"a}l{\"a}inen, Mika and H{\`a} M{\~y}, Linh and Han, Na-Rae and Harris, Kim and Haug, Dag and Heinecke, Johannes and Hennig, Felix and Hladk{\'a}, Barbora and Hlav{\'a}{\v c}ov{\'a}, Jaroslava and Hociung, Florinel and Hohle, Petter and Hwang, Jena and Ikeda, Takumi and Ion, Radu and Irimia, Elena and Ishola, {\d O}l{\'a}j{\'{\i}}d{\'e} and Jel{\'{\i}}nek, Tom{\'a}{\v s} and Johannsen, Anders and J{\o}rgensen, Fredrik and Juutinen, Markus and Ka{\c s}{\i}kara, H{\"u}ner and Kaasen, Andre and Kabaeva, Nadezhda and Kahane, Sylvain and Kanayama, Hiroshi and Kanerva, Jenna and Katz, Boris and Kayadelen, Tolga and Kenney, Jessica and Kettnerov{\'a}, V{\'a}clava and Kirchner, Jesse and Klementieva, Elena and K{\"o}hn, Arne and Kopacewicz, Kamil and Kotsyba, Natalia and Kovalevskait{\.e}, Jolanta and Krek, Simon and Kwak, Sookyoung and Laippala, Veronika and Lambertino, Lorenzo and Lam, Lucia and Lando, Tatiana and Larasati, Septina Dian and Lavrentiev, Alexei and Lee, John and L{\^e} H{\`{\^o}}ng, Phương and Lenci, Alessandro and Lertpradit, Saran and Leung, Herman and Li, Cheuk Ying and Li, Josie and Li, Keying and Lim, {KyungTae} and Liovina, Maria and Li, Yuan and Ljube{\v s}i{\'c}, Nikola and Loginova, Olga and Lyashevskaya, Olga and Lynn, Teresa and Macketanz, Vivien and Makazhanov, Aibek and Mandl, Michael and Manning, Christopher and Manurung, Ruli and M{\u a}r{\u a}nduc, C{\u a}t{\u a}lina and Mare{\v c}ek, David and Marheinecke, Katrin and Mart{\'{\i}}nez Alonso, H{\'e}ctor and Martins, Andr{\'e} and Ma{\v s}ek, Jan and Matsumoto, Yuji and {McDonald}, Ryan and {McGuinness}, Sarah and Mendon{\c c}a, Gustavo and Miekka, Niko and Misirpashayeva, Margarita and Missil{\"a}, Anna and Mititelu, C{\u a}t{\u a}lin and Mitrofan, Maria and Miyao, Yusuke and Montemagni, Simonetta and More, Amir and Moreno Romero, Laura and Mori, Keiko Sophie and Morioka, Tomohiko and Mori, Shinsuke and Moro, Shigeki and Mortensen, Bjartur and Moskalevskyi, Bohdan and Muischnek, Kadri and Munro, Robert and Murawaki, Yugo and M{\"u}{\"u}risep, Kaili and Nainwani, Pinkey and Navarro Hor{\~n}iacek, Juan Ignacio and Nedoluzhko, Anna and Ne{\v s}pore-B{\=e}rzkalne, Gunta and Nguy{\~{\^e}}n Th{\d i}, Lương and Nguy{\~{\^e}}n Th{\d i} Minh, Huy{\`{\^e}}n and Nikaido, Yoshihiro and Nikolaev, Vitaly and Nitisaroj, Rattima and Nurmi, Hanna and Ojala, Stina and Ojha, Atul Kr. and Ol{\'u}{\`o}kun, Ad{\'e}day{\d o}̀ and Omura, Mai and Osenova, Petya and {\"O}stling, Robert and {\O}vrelid, Lilja and Partanen, Niko and Pascual, Elena and Passarotti, Marco and Patejuk, Agnieszka and Paulino-Passos, Guilherme and Peljak-{\L}api{\'n}ska, Angelika and Peng, Siyao and Perez, Cenel-Augusto and Perrier, Guy and Petrova, Daria and Petrov, Slav and Phelan, Jason and Piitulainen, Jussi and Pirinen, Tommi A and Pitler, Emily and Plank, Barbara and Poibeau, Thierry and Ponomareva, Larisa and Popel, Martin and Pretkalni{\c n}a, Lauma and Pr{\'e}vost, Sophie and Prokopidis, Prokopis and Przepi{\'o}rkowski, Adam and Puolakainen, Tiina and Pyysalo, Sampo and Qi, Peng and R{\"a}{\"a}bis, Andriela and Rademaker, Alexandre and Ramasamy, Loganathan and Rama, Taraka and Ramisch, Carlos and Ravishankar, Vinit and Real, Livy and Reddy, Siva and Rehm, Georg and Riabov, Ivan and Rie{\ss}ler, Michael and Rimkut{\.e}, Erika and Rinaldi, Larissa and Rituma, Laura and Rocha, Luisa and Romanenko, Mykhailo and Rosa, Rudolf and Rovati, Davide and Roșca, Valentin and Rudina, Olga and Rueter, Jack and Sadde, Shoval and Sagot, Beno{\^{\i}}t and Saleh, Shadi and Salomoni, Alessio and Samard{\v z}i{\'c}, Tanja and Samson, Stephanie and Sanguinetti, Manuela and S{\"a}rg, Dage and Saul{\={\i}}te, Baiba and Sawanakunanon, Yanin and Schneider, Nathan and Schuster, Sebastian and Seddah, Djam{\'e} and Seeker, Wolfgang and Seraji, Mojgan and Shen, Mo and Shimada, Atsuko and Shirasu, Hiroyuki and Shohibussirri, Muh and Sichinava, Dmitry and Silveira, Aline and Silveira, Natalia and Simi, Maria and Simionescu, Radu and Simk{\'o}, Katalin and {\v S}imkov{\'a}, M{\'a}ria and Simov, Kiril and Smith, Aaron and Soares-Bastos, Isabela and Spadine, Carolyn and Stella, Antonio and Straka, Milan and Strnadov{\'a}, Jana and Suhr, Alane and Sulubacak, Umut and Suzuki, Shingo and Sz{\'a}nt{\'o}, Zsolt and Taji, Dima and Takahashi, Yuta and Tamburini, Fabio and Tanaka, Takaaki and Tellier, Isabelle and Thomas, Guillaume and Torga, Liisi and Trosterud, Trond and Trukhina, Anna and Tsarfaty, Reut and Tyers, Francis and Uematsu, Sumire and Ure{\v s}ov{\'a}, Zde{\v n}ka and Uria, Larraitz and Uszkoreit, Hans and Utka, Andrius and Vajjala, Sowmya and van Niekerk, Daniel and van Noord, Gertjan and Varga, Viktor and Villemonte de la Clergerie, Eric and Vincze, Veronika and Wallin, Lars and Walsh, Abigail and Wang, Jing Xian and Washington, Jonathan North and Wendt, Maximilan and Williams, Seyi and Wir{\'e}n, Mats and Wittern, Christian and Woldemariam, Tsegay and Wong, Tak-sum and Wr{\'o}blewska, Alina and Yako, Mary and Yamazaki, Naoki and Yan, Chunxiao and Yasuoka, Koichi and Yavrumyan, Marat M. and Yu, Zhuoran and {\v Z}abokrtsk{\'y}, Zden{\v e}k and Zeldes, Amir and Zhang, Manying and Zhu, Hanzhi},<br>
url={http://hdl.handle.net/11234/1-3105},<br>
note={{LINDAT}/{CLARIAH}-{CZ} digital library at the Institute of Formal and Applied Linguistics ({{\'U}FAL}), Faculty of Mathematics and Physics, Charles University},<br>
copyright={Licence Universal Dependencies v2.5},<br>
year={2019}<br>
}<br><br>
@article{Sang2003IntroductionTT,<br>
title={Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition},<br>
author={Erik F. Tjong Kim Sang and Fien De Meulder},<br>
journal={ArXiv},<br>
year={2003},<br>
volume={cs.CL/0306050}<br>
}<br><br>
@article{Sang2002IntroductionTT,<br>
title={Introduction to the CoNLL-2002 Shared Task: Language-Independent Named Entity Recognition},<br>
author={Erik F. Tjong Kim Sang},<br>
journal={ArXiv},<br>
year={2002},<br>
volume={cs.CL/0209010}<br>
}<br><br>
@inproceedings{Conneau2018XNLIEC,<br>
title={XNLI: Evaluating Cross-lingual Sentence Representations},<br>
author={Alexis Conneau and Guillaume Lample and Ruty Rinott and Adina Williams and Samuel R. Bowman and Holger Schwenk and Veselin Stoyanov},<br>
booktitle={EMNLP},<br>
year={2018}<br>
}<br><br>
@article{Lewis2019MLQAEC,<br>
title={MLQA: Evaluating Cross-lingual Extractive Question Answering},<br>
author={Patrick Lewis and Barlas Oguz and Ruty Rinott and Sebastian Riedel and Holger Schwenk},<br>
journal={ArXiv},<br>
year={2019},<br>
volume={abs/1910.07475}<br>
}<br><br>
@article{Yang2019PAWSXAC,<br>
title={PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification},<br>
author={Yinfei Yang and Yuan Zhang and Chris Tar and Jason Baldridge},<br>
journal={ArXiv},<br>
year={2019},<br>
volume={abs/1908.11828}<br>
}<br><br></code></div>
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