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@ -31,7 +31,7 @@ Gigaword `\cite{rush2015neural}` contains 4M examples extracted from the news ar
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#### XSUM
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#### XSUM
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XSUM `\cite{narayan2018don}` consists of 227K online articles from the British Broadcasting Corporation (BBC), which contains professionally written single-sentence summaries. After the pre-processing, there are 226,677 <article, summary> data pairs, where the source input is the the news article, and the target output is a single summary sentence. ROUGE-1, ROUGE-2, and ROUGE-L are used as the metrics.
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XSUM `\cite{narayan2018don}` consists of 227K online articles from the British Broadcasting Corporation (BBC), which contains professionally written single-sentence summaries. After the pre-processing, there are 226,677 <article, summary> data pairs, where the source input is the the news article, and the target output is a single summary sentence. ROUGE-1, ROUGE-2, and ROUGE-L are used as the metrics.
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### MSNews
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#### MSNews
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We collect 202K online news articles from a real world search engine. Each article contains a professionally written single-sentence headline. After the pre-processing, there are 201,947 <article, headline> data pairs, where the source input is the news article, and the target output is a news headline. ROUGE-1, ROUGE-2, and ROUGE-L are used as the evaluation metrics.
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We collect 202K online news articles from a real world search engine. Each article contains a professionally written single-sentence headline. After the pre-processing, there are 201,947 <article, headline> data pairs, where the source input is the news article, and the target output is a news headline. ROUGE-1, ROUGE-2, and ROUGE-L are used as the evaluation metrics.
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### Answer-aware Question Generation Tasks
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### Answer-aware Question Generation Tasks
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@ -57,7 +57,7 @@ In order to use our dataset, please navigate to [GLGE Leaderboard](https://micro
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## Get Baselines
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## Get Baselines
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We put the baselines to ProphetNet [repo](https://github.com/microsoft/ProphetNet). It contains the pre-trained models, fine-tuning scripts, and evaluation scripts for GLGE.
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We put the baselines to ProphetNet [repo](https://github.com/microsoft/ProphetNet/GLGE_baselines). It contains the pre-trained models, fine-tuning scripts, and evaluation scripts for GLGE.
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## Leaderboard Submission
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## Leaderboard Submission
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</div>
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</div>
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<div class="row" style="color:red;">
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<div class="row" style="color:red;">
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<ul>
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<ul>
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<li>2020-11-02: We update the evaluation scripts and ProphetNet baselines on <a href="https://github.com/microsoft/ProphetNet">Link</a>.</li>
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<li>2020-11-02: We update the evaluation scripts and ProphetNet baselines on <a href="https://github.com/microsoft/ProphetNet/GLGE_baselines">Link</a>.</li>
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</ul>
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</ul>
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<p></p>
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<p></p>
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</div>
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</div>
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<h4>Relevant Links</h4>
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<h4>Relevant Links</h4>
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<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://github.com/microsoft/GLGE">GLGE Submission Guideline/Github</a>
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<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://github.com/microsoft/GLGE">GLGE Submission Guideline/Github</a>
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<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://arxiv.org/abs/">GLGE Paper</a>
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<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://arxiv.org/abs/">GLGE Paper</a>
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<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://github.com/microsoft/ProphetNet">ProphetNet Baseline</a>
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<a class="btn btn-primary btn-md" style='margin-right: 3px;' href="https://github.com/microsoft/ProphetNet/GLGE_baselines">ProphetNet Baseline</a>
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<div class="row"> </div>
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<div class="row"> </div>
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<div id="glgedata"> </div>
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<div id="glgedata"> </div>
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<div class="row"> </div>
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<div class="row"> </div>
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