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<!DOCTYPE html>
<html>
<head>
<link rel="stylesheet" type="text/css" href="css/bootstrap.css">
<link rel="stylesheet" type="text/css" href="css/style.css">
<link href="https://fonts.googleapis.com/css?family=Raleway:100,200,300,400,500,600,700,800,900" rel="stylesheet">
<link rel="stylesheet" href="css/fontAwesome.css">
<title> WebSRC - A Dataset For Web-Based Structual Reading Comprehension </title>
</head>
<body>
<header class="header">
<div class="container clearfix">
<div class="left-container">
<a href="#"> WebSRC </a>
</div>
<div class="right-container">
<ul class="nav-menu clearfix">
<li>
<a href="#"> Home </a>
<li>
<li>
<a href="dashboard.html"> Explore v1.0 </a>
</li>
</ul>
</div>
</div>
</header>
<section class="banner">
<div class="container clearfix">
<h1> WebSRC </h1>
<span> A Dataset For Web-Based Structual Reading Comprehension </span>
<a href="https://websrc-data.s3.amazonaws.com/release.zip" class="download-hyperlink"><button class="download-button">
<i class="fa fa-arrow-circle-o-down" aria-hidden="true"></i> Download
</button>
</a>
</div>
</section>
<section class="main-content">
<div class="container clearfix">
<div class="row">
<div class="col-md-5">
<div class="info-container">
<span class="info-title">
<i class="fa fa-info-circle" aria-hidden="true"></i>
What is WebSRC?
</span>
<p>
WebSRC is a novel <strong>Web</strong>-based <strong>S</strong>tructural <strong>R</strong>eading <strong>C</strong>omprehension dataset. It consists of 0.44M question-answer pairs, which are collected from 6.5K web pages with corresponding HTML source code, screenshots and metadata. Each question in WebSRC requires a certain structural understanding of a web page to answer, and the answer is either a text span on the web page or yes/no.
</p>
<button class="action-button" style="display: none;">
Button 1
</button>
<button class="inverse-button" style="display: none;">
Button 2
</button>
<span class="info-title">
<i class="fa fa-star-o" aria-hidden="true"></i>
News
</span>
<p class="row">
<span class="news-date col-md-2"> Aug 27, 2022 </span>
<span class="news-context"> To access the test set, see <a href="https://github.com/X-LANCE/WebSRC-Baseline#obtain-test-result">here</a> </span>
<span class="news-date col-md-2"> Sept 1, 2021 </span>
<span class="news-context"> The full dataset and baseline is available in: </span>
<a href="https://pan.baidu.com/s/1-sqWgc8bTm6-bkAFYJwYQQ" class="download-link">
<i class="fa fa-cloud-download" aria-hidden="true"></i>
Extraction code: <strong>2mys</strong>
</a>
<a href="https://websrc-data.s3.amazonaws.com/release.zip" class="download-link">
<i class="fa fa-amazon" aria-hidden="true"></i>
Download from Amazon.com
</a>
<span class="news-date col-md-2"> Aug 25, 2021 </span>
<span class="news-context"> Our paper is accepted by EMNLP 2021, the updated version of dataset will be available soon. </span>
<span class="news-context"> Baseline is available on </span>
<a href="https://github.com/X-LANCE/WebSRC-Baseline" class="download-link">
<i class="fa fa-github" aria-hidden="true"></i>
WebSRC-Baseline
</a>
</p>
<span class="info-title">
<i class="fa fa-question-circle-o" aria-hidden="true"></i>
Contact Us
</span>
<p>
If you have any questions about this dataset, please contact
<a href="mailto:[email protected]">[email protected]</a> or
<a href="mailto:[email protected]">[email protected]</a>
</p>
</div>
</div>
<div class="col-md-7">
<div class="info-container">
<span class="info-title">
<i class="fa fa-bar-chart" aria-hidden="true"></i>
Leaderboard
</span>
<p>
Three metrics, i.e. Exact Match (EM), F1 score, and Path Overlap Score (POS), are used to evaluate on the test set of WebSRC. Please refer to the paper to find more details about evaluation metrics.
</p>
<table class="leader-board">
<tbody>
<tr>
<th> Rank </th>
<th> Model </th>
<th> EM </th>
<th> F1 </th>
<th> POS </th>
</tr>
<tr>
<td>
1
<span>
Sep 4, 2023
</span>
</td>
<td>
SageGPT-small-v0.2
<p> 4paradigm.Inc </p>
</td>
<td class="stat"> 89.11 </td>
<td class="stat"> 92.15 </td>
<td class="stat"> N/A </td>
</tr>
<tr>
<td>
2
<span>
Jan 12, 2024
</span>
</td>
<td>
ScreenAI 5B
<p> Google Research </p>
<a class='link' href='https://arxiv.org/abs/2402.04615'> (Baechler et al.) </a>
<!-- <a class='link' href='https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/ernie-layoutx'> code </a>
<a class='link' href='https://huggingface.co/spaces/PaddlePaddle/ERNIE-LayoutX'> demo </a> -->
</td>
<td class="stat"> 84.02 </td>
<td class="stat"> 87.24 </td>
<td class="stat"> N/A </td>
</tr>
<tr>
<td>
3
<span>
Oct 12, 2022
</span>
</td>
<td>
DocPrompt (ErnieLayout-Large)
<p> BAIDU-Document Intelligence </p>
<a class='link' href='https://arxiv.org/abs/2308.10959'> (Wu et al.) </a>
<a class='link' href='https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/ernie-layoutx'> code </a>
<a class='link' href='https://huggingface.co/spaces/PaddlePaddle/ERNIE-LayoutX'> demo </a>
</td>
<td class="stat"> 77.35 </td>
<td class="stat"> 85.04 </td>
<td class="stat"> N/A </td>
</tr>
<tr>
<td>
4
<span>
Mar 01, 2022
</span>
</td>
<td>
TIE (MarkupLM-Large)
<p> Shanghai Jiao Tong University </p>
<a class='link' href='https://arxiv.org/abs/2205.06435'> (Zhao et al., NAACL'22) </a>
<a class='link' href='https://github.com/X-LANCE/TIE'> code </a>
</td>
<td class="stat"> 76.25 </td>
<td class="stat"> 80.51 </td>
<td class="stat"> 89.50 </td>
</tr>
<tr>
<td>
5
<span>
Mar 01, 2022
</span>
</td>
<td>
TIE (MarkupLM-Large)-3_seeds_ave
<p> Shanghai Jiao Tong University </p>
<a class='link' href='https://arxiv.org/abs/2205.06435'> (Zhao et al., NAACL'22) </a>
<a class='link' href='https://github.com/X-LANCE/TIE'> code </a>
</td>
<td class="stat"> 75.87 </td>
<td class="stat"> 80.19 </td>
<td class="stat"> 89.73 </td>
</tr>
<tr>
<td>
6
<span>
Nov 30, 2021
</span>
</td>
<td>
MarkupLM-Large
<p> MSRA+SJTU </p>
<a class='link' href='https://arxiv.org/abs/2110.08518'> (Li et al., ACL'22) </a>
<a class='link' href='https://github.com/microsoft/unilm/tree/master/markuplm'> code </a>
</td>
<td class="stat"> 69.87 </td>
<td class="stat"> 77.94 </td>
<td class="stat"> 88.09 </td>
</tr>
<tr>
<td>
7
<span>
Nov 30, 2021
</span>
</td>
<td>
MarkupLM-Large (3_seeds_ave)
<p> MSRA+SJTU </p>
<a class='link' href='https://arxiv.org/abs/2110.08518'> (Li et al., ACL'22) </a>
<a class='link' href='https://github.com/microsoft/unilm/tree/master/markuplm'> code </a>
</td>
<td class="stat"> 69.09 </td>
<td class="stat"> 76.45 </td>
<td class="stat"> 87.24 </td>
</tr>
<tr>
<td>
8
<span>
Sept 01, 2021
</span>
</td>
<td>
V-PLM (ELECTRA)
<p> Shanghai Jiao Tong University </p>
<a class='link' href='https://arxiv.org/abs/2101.09465'> (Chen et al., EMNLP'21) </a>
<a class='link' href='https://github.com/X-LANCE/WebSRC-Baseline'> code </a>
</td>
<td class="stat"> 68.07 </td>
<td class="stat"> 75.25 </td>
<td class="stat"> 84.96 </td>
</tr>
<tr>
<td>
9
<span>
Sept 01, 2021
</span>
</td>
<td>
V-PLM (BERT)
<p> Shanghai Jiao Tong University </p>
<a class='link' href='https://arxiv.org/abs/2101.09465'> (Chen et al., EMNLP'21) </a>
<a class='link' href='https://github.com/X-LANCE/WebSRC-Baseline'> code </a>
</td>
<td class="stat"> 54.84 </td>
<td class="stat"> 62.80 </td>
<td class="stat"> 76.39 </td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
</section>
<section class="footer clearfix">
<a href="http://x-lance.sjtu.edu.cn/"> SJTU X-LANCE Lab<a>
</section>
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</body>
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