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<p>The two-click<a href="#" data-mdb-toggle="tooltip" title="What are the two clicks, you ask? Copy and paste!"><sup>*</sup></a> reproduction matrix below provides commands for reproducing experimental results reported in a number of papers, denoted by the references in square brackets.
Instructions for programmatic execution are shown at the bottom of this page (scroll down).</p>

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        <th class="headertop" colspan="4"><b>TREC 2019</b></th>
        <th class="headertop" colspan="4"><b>TREC 2020</b></th>
        <th class="headertop" colspan="3"><b>dev</b></th>
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        <th class="headerbottom" scope="col"><br/>AP</th>
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        <th class="headerbottom" scope="col">R@1K</th>
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        <th class="headerbottom" scope="col"><br/>AP</th>
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        <th class="headerbottom" scope="col">RR@10</th>
        <th class="headerbottom" scope="col">R@1K</th>

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$rows

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<ul style="list-style-type:none; padding-top: 25px">

<li><p>[1] Xueguang Ma, Ronak Pradeep, Rodrigo Nogueira, and Jimmy Lin.
<a href="https://cs.uwaterloo.ca/~jimmylin/publications/Ma_etal_SIGIR2022.pdf">Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2.</a>
<i>Proceedings of the 45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022)</i>, July 2022.</p>

<p>&nbsp; &nbsp; &nbsp; &nbsp;Numbers in parentheses correspond to rows in Table 1 of the paper.</p></li>

<li><p>[2] Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N. Bennett, Junaid Ahmed, and Arnold Overwijk.
<a href="https://openreview.net/forum?id=zeFrfgyZln">Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval.</a>
<i>Proceedings of the 9th International Conference on Learning Representations (ICLR 2021), May 2021.</i></p></li>

<li><p>[3] Sebastian Hofstätter, Sophia Althammer, Michael Schröder, Mete Sertkan, and Allan Hanbury.
<a href="https://arxiv.org/abs/2010.02666">Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation.</a>
<i>arXiv:2010.02666</i>, October 2020.</p></li>

<li><p>[4] Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, and Allan Hanbury.
<a href="https://dl.acm.org/doi/10.1145/3404835.3462891">Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling.</a>
<i>Proceedings of the 44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021)</i>, pages 113-122, July 2021.</p></li>

<li><p>[5] Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin.
<a href="https://aclanthology.org/2021.repl4nlp-1.17/">In-Batch Negatives for Knowledge Distillation with Tightly-Coupled Teachers for Dense Retrieval.</a>
<i>Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021)</i>, pages 163-173, August 2021.</p></li>

</ul>

<div style="padding-top: 20px"/>

<h4>Programmatic Execution</h4>

<p>All experimental runs shown in the above table can be programmatically executed based on the instructions below.
To list all the experimental conditions:</p>

<blockquote class="mycode2"><tt>
python -m pyserini.2cr.msmarco --collection v1-passage --list-conditions
</tt></blockquote>

<p>These conditions correspond to the table rows above.</p>

<p>For all conditions, just show the commands in a "dry run":</p>

<blockquote class="mycode2"><tt>
python -m pyserini.2cr.msmarco --collection v1-passage --all --display-commands --dry-run
</tt></blockquote>

<p>To actually run all the experimental conditions:</p>

<blockquote class="mycode2"><tt>
python -m pyserini.2cr.msmarco --collection v1-passage --all --display-commands
</tt></blockquote>

<p>With the above command, run files will be placed in the current directory.
Use the option <tt>--directory runs/</tt> to place the runs in a sub-directory.</p>

<p>To show the commands for a specific condition:</p>

<blockquote class="mycode2"><tt>
python -m pyserini.2cr.msmarco --collection v1-passage --condition bm25-default --display-commands --dry-run
</tt></blockquote>

<p>This will generate exactly the commands for a specific condition above (corresponding to a row in the table).</p>

<p>To actually run a specific condition:</p>

<blockquote class="mycode2"><tt>
python -m pyserini.2cr.msmarco --collection v1-passage --condition bm25-default --display-commands
</tt></blockquote>

<p>Again, with the above command, run files will be placed in the current directory.
Use the option <tt>--directory runs/</tt> to place the runs in a sub-directory.</p>

<p>Finally, to generate this page:</p>

<blockquote class="mycode2"><tt>
python -m pyserini.2cr.msmarco --collection v1-passage --generate-report --output msmarco-v1-passage.html
</tt></blockquote>

<p>The output file <tt>msmarco-v1-passage.html</tt> should be identical to this page.</p>

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