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<!DOCTYPE html>
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<h1 class="title is-1 publication-title">Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://thakur-nandan.github.io/" target="_blank">Nandan Thakur</a>,<sup>1</sup></span>
<span class="author-block">
<a href="https://cs.uwaterloo.ca/~jimmylin/" target="_blank">Jimmy Lin</a>,<sup>1</sup></span>
<span class="author-block">
<a href="https://www.samuelhavens.com/" target="_blank">Sam Havens</a>,<sup>2</sup></span>
<span class="author-block">
<a href="https://people.csail.mit.edu/mcarbin/" target="_blank">Michael Carbin</a>,<sup>2</sup></span>
<span class="author-block">
<a href="https://omarkhattab.com/" target="_blank">Omar Khattab</a>,<sup>2</sup></span>
<span class="author-block">
<a href="https://mrdrozdov.github.io/" target="_blank">Andrew Drozdov</a><sup>2</sup>
</span>
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<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>University of Waterloo <sup>2</sup>Databricks<br>
NeurIPS 2025 Dataset & Benchmark Track<br>
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<span class="tldr-label">TL;DR</span>
<span class="tldr-text">FreshStack is a holistic framework for building realistic & challenging RAG benchmarks from community-asked questions and answers on niche and fast-growing domains.</span>
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<h2 class="section-title">Latest News</h2>
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<li class="news-item">
<span class="news-date">Sep 2026</span>
<span class="news-icon">🎉</span>
<span class="news-text">Our work on analyzing technical drift on LangChain has been <strong>accepted at EMNLP 2026 (Findings Track)</strong>.</span>
</li>
<li class="news-item">
<span class="news-date">Mar 2026</span>
<span class="news-icon">📊</span>
<span class="news-text">A new preprint on analysing temporal drift in technical documentation in FreshStack (LangChain domain): <strong><a href="https://arxiv.org/abs/2603.04532" target="_blank" rel="noopener">arxiv.org/abs/2603.04532</a></strong>.</span>
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<span class="news-date">Mar 2026</span>
<span class="news-icon">📊</span>
<span class="news-text"><strong><a href="https://www.databricks.com/blog/meet-karl-faster-agent-enterprise-knowledge-powered-custom-rl" target="_blank" rel="noopener">KARLBench</a></strong>, a recently released benchmark by Databricks, has incorporated FreshStack as one of its datasets.</span>
</li>
<li class="news-item">
<span class="news-date">Nov 2025</span>
<span class="news-icon">🏅</span>
<span class="news-text"><strong>FreshStack</strong> received the Honourable Mention for the award of <strong><a href="https://www.bcs.org/membership-and-registrations/member-communities/information-retrieval-specialist-group/awards/bcs-search-industry-awards/" target="_blank" rel="noopener">Best Search Project in 2025</a></strong> at the BCS Search Solutions event held in London.</span>
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<span class="news-date">Sep 2025</span>
<span class="news-icon">🎯</span>
<span class="news-text">Our roadmap is focused on evaluating new embedding models with extensions to ColBERT-style models soon!</span>
</li>
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<span class="news-date">Sep 2025</span>
<span class="news-icon">🎉</span>
<span class="news-text">Our paper <strong>FreshStack</strong> has been <strong>accepted at NeurIPS 2025 (Datasets & Benchmarks Track)</strong>. Camera-ready to come soon!</span>
</li>
<li class="news-item is-older">
<span class="news-date">Sep 2025</span>
<span class="news-icon">📌</span>
<span class="news-text"><strong>FreshStack</strong> has now been officially included in <strong><a href="https://huggingface.co/blog/rteb" target="_blank" rel="noopener">RTEB (Retrieval Embedding Benchmark)</a></strong>, a newer version of the popular MTEB benchmark.</span>
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<h2 class="leaderboard-title">🏆 FreshStack Leaderboard</h2>
<p class="leaderboard-subtitle">
Zero-shot retrieval on five niche technical domains (October 2024 snapshot), ranked by average <b>Recall@50</b>.
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<span class="lb-legend-item" title="alpha-nDCG@10: retrieval diversity & relevance"><b>α@10</b> alpha-nDCG · diversity & relevance</span>
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<th colspan="5" class="model-group-cell"></th>
<th colspan="3" class="average-details-cell">Avg. (5)</th>
<th colspan="3" class="langchain-details-cell">LangChain</th>
<th colspan="3" class="yolo-details-cell">Yolo v7 & v8</th>
<th colspan="3" class="laravel-details-cell">Laravel 10 & 11</th>
<th colspan="3" class="angular-details-cell">Angular 16, 17 & 18</th>
<th colspan="3" class="godot-details-cell">Godot4</th>
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<th>#</th>
<th class="sortable" data-key="name">Retriever</th>
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<th class="sortable" data-key="size">Size</th>
<th class="sortable" data-key="date">Date</th>
<th class="average-details sortable" data-key="average.alpha_ndcg_10">α@10</th>
<th class="average-details sortable" data-key="average.coverage_20">C@20</th>
<th class="average-details sortable" data-key="average.recall_50">R@50</th>
<th class="langchain-details sortable" data-key="langchain.alpha_ndcg_10">α@10</th>
<th class="langchain-details sortable" data-key="langchain.coverage_20">C@20</th>
<th class="langchain-details sortable" data-key="langchain.recall_50">R@50</th>
<th class="yolo-details sortable" data-key="yolo.alpha_ndcg_10">α@10</th>
<th class="yolo-details sortable" data-key="yolo.coverage_20">C@20</th>
<th class="yolo-details sortable" data-key="yolo.recall_50">R@50</th>
<th class="laravel-details sortable" data-key="laravel.alpha_ndcg_10">α@10</th>
<th class="laravel-details sortable" data-key="laravel.coverage_20">C@20</th>
<th class="laravel-details sortable" data-key="laravel.recall_50">R@50</th>
<th class="angular-details sortable" data-key="angular.alpha_ndcg_10">α@10</th>
<th class="angular-details sortable" data-key="angular.coverage_20">C@20</th>
<th class="angular-details sortable" data-key="angular.recall_50">R@50</th>
<th class="godot-details sortable" data-key="godot.alpha_ndcg_10">α@10</th>
<th class="godot-details sortable" data-key="godot.coverage_20">C@20</th>
<th class="godot-details sortable" data-key="godot.recall_50">R@50</th>
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<div class="lb-info-grid">
<div class="lb-info-card">
<div class="lb-info-icon">🧪</div>
<h3>Evaluation setup</h3>
<ul>
<li><b>Zero-shot</b> retrieval of relevant document chunks given a query, on FreshStack (<b>October 2024</b> version).</li>
<li>Open-source & proprietary <b>single-vector</b> embedding models, plus <b>late-interaction</b> (multi-vector, ColBERT-style) retrievers.</li>
<li>Maximum sequence length of <b>2048 tokens</b> for all models for both query and document.</li>
</ul>
</div>
<div class="lb-info-card">
<div class="lb-info-icon">📚</div>
<h3>Five datasets</h3>
<div class="lb-domain-tags">
<span>LangChain</span><span>Yolo v7 & v8</span><span>Laravel 10 & 11</span><span>Angular 16, 17 & 18</span><span>Godot4</span>
</div>
<p class="lb-info-tip">💡 Queries in FreshStack can be <b>pretty long</b>, so use a model that can handle code and long queries.</p>
</div>
<div class="lb-info-card lb-info-card--cta">
<div class="lb-info-icon">🚀</div>
<h3>Submit your model</h3>
<p>Add your results to <code>leaderboard_data.json</code> and open a pull request.</p>
<a class="button is-rounded lb-cta-button" href="https://github.com/fresh-stack/fresh-stack.github.io/blob/master/leaderboard_data.json" target="_blank" rel="noopener">
<span class="icon"><i class="fab fa-github"></i></span><span>Open leaderboard_data.json</span>
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</section>
<!-- End Leaderboard -->
<!-- Paper abstract -->
<section class="section page-section" id="abstract">
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<span class="section-kicker">Paper</span>
<h2 class="section-title">Abstract</h2>
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<div class="content-card section-text has-text-justified">
<p>
We introduce FreshStack, a reusable framework for automatically building information retrieval (IR) evaluation benchmarks from community-asked questions and answers.
FreshStack conducts the following steps: (1) automatic corpus collection from code and technical documentation, (2) nugget generation from community-asked questions and answers, and (3) nugget-level support, retrieving documents using a fusion of retrieval techniques and hybrid architectures.
We use FreshStack to build five datasets on fast-growing, recent, and niche topics to ensure the tasks are sufficiently challenging.
Existing retrieval models, when applied out-of-the-box, significantly underperform oracle approaches on all five topics, denoting plenty of headroom to improve IR quality.
</p>
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</section>
<!-- End paper abstract -->
<!-- Overview: pipeline steps + video -->
<section class="section page-section is-tinted" id="overview">
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<div class="section-heading">
<span class="section-kicker">Framework</span>
<h2 class="section-title">How FreshStack Works</h2>
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<div class="steps-grid">
<div class="step-card">
<div class="step-number">1</div>
<div class="step-icon"><i class="fas fa-code"></i></div>
<h3 class="step-title">Corpus Collection</h3>
<p class="step-text">Automatically collect a corpus from code and technical documentation.</p>
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<div class="step-card">
<div class="step-number">2</div>
<div class="step-icon"><i class="fas fa-lightbulb"></i></div>
<h3 class="step-title">Nugget Generation</h3>
<p class="step-text">Generate nuggets from community-asked questions and answers.</p>
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<div class="step-card">
<div class="step-number">3</div>
<div class="step-icon"><i class="fas fa-search"></i></div>
<h3 class="step-title">Nugget-level Support</h3>
<p class="step-text">Retrieve documents with a fusion of retrieval techniques and hybrid architectures to support each nugget.</p>
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</div>
<div class="video-card">
<video poster="" id="video1" autoplay controls muted loop playsinline>
<source src="static/videos/teaser.mp4" type="video/mp4">
</video>
<p class="video-caption">Step-by-step procedure followed in FreshStack for constructing evaluation datasets.</p>
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</section>
<!-- End overview -->
<!-- Metrics vs. parameters -->
<section class="section page-section" id="avg-metric-plots">
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<span class="section-kicker">Analysis</span>
<h2 class="section-title">Metrics vs. Model Parameters</h2>
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<div class="content section-text has-text-justified">
<p>
Each point is a model with <strong>model parameters</strong> in the leaderboard (parameters in millions or billions, parsed from values such as <code>7B</code> or <code>434M</code>).
The <strong>y</strong>-axis is the <strong>average across the five FreshStack domains</strong> for <strong>α@10</strong> (alpha-nDCG@10), <strong>C@20</strong> (Coverage@20) and <strong>R@50</strong> (Recall@50).
Models without a disclosed size (shown as “-” in the table) are listed below the plot and appear only in the release-date plot.
Marker colors group model families (the <code>family</code> field in <code>leaderboard_data.json</code>). Models released in the last 90 days are <strong>outlined and labeled</strong>.
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<p id="recall-plots-empty" class="has-text-centered is-hidden help is-info" style="margin-bottom: 1rem;"></p>
<div class="plot-card" data-plot-tabs>
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<span class="plot-card-title">Avg. (5 domains) vs. parameters</span>
<div class="plot-tabs" role="tablist">
<button type="button" class="plot-tab" role="tab" data-target="plot-avg-alpha10">α-nDCG@10</button>
<button type="button" class="plot-tab" role="tab" data-target="plot-avg-c20">Coverage@20</button>
<button type="button" class="plot-tab is-active" role="tab" data-target="plot-avg-r50">Recall@50</button>
</div>
</div>
<div id="plot-avg-alpha10" class="recall-param-plot plot-pane" aria-label="Average alpha-nDCG at 10 versus parameters"></div>
<div id="plot-avg-c20" class="recall-param-plot plot-pane" aria-label="Average Coverage at 20 versus parameters"></div>
<div id="plot-avg-r50" class="recall-param-plot plot-pane is-active" aria-label="Average Recall at 50 versus parameters"></div>
<div id="recall-plots-omitted" class="plot-omitted is-hidden"></div>
</div>
</div>
</section>
<!-- Metrics vs. release date -->
<section class="section page-section is-tinted" id="avg-metric-date-plots">
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<div class="section-heading">
<span class="section-kicker">Analysis</span>
<h2 class="section-title">Metrics vs. Model Release Date</h2>
</div>
<div class="content section-text has-text-justified">
<p>
Each point is a model with a valid <strong>release date</strong> in the leaderboard.
The <strong>y</strong>-axis is the <strong>average across the five FreshStack domains</strong> for
<strong>α@10</strong> (alpha-nDCG@10), <strong>C@20</strong> (Coverage@20), and <strong>R@50</strong> (Recall@50).
Marker colors group model families (the <code>family</code> field in <code>leaderboard_data.json</code>). Models released in the last 90 days are <strong>outlined and labeled</strong>.
</p>
</div>
<p id="date-plots-empty" class="has-text-centered is-hidden help is-info" style="margin-bottom: 1rem;"></p>
<div class="plot-card" data-plot-tabs>
<div class="plot-card-header">
<span class="plot-card-title">Avg. (5 domains) vs. release date</span>
<div class="plot-tabs" role="tablist">
<button type="button" class="plot-tab" role="tab" data-target="plot-date-avg-alpha10">α-nDCG@10</button>
<button type="button" class="plot-tab" role="tab" data-target="plot-date-avg-c20">Coverage@20</button>
<button type="button" class="plot-tab is-active" role="tab" data-target="plot-date-avg-r50">Recall@50</button>
</div>
</div>
<div id="plot-date-avg-alpha10" class="recall-param-plot plot-pane" aria-label="Average alpha-nDCG at 10 versus model release date"></div>
<div id="plot-date-avg-c20" class="recall-param-plot plot-pane" aria-label="Average Coverage at 20 versus model release date"></div>
<div id="plot-date-avg-r50" class="recall-param-plot plot-pane is-active" aria-label="Average Recall at 50 versus model release date"></div>
</div>
</div>
</section>
<!-- Poster Section -->
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<span class="section-kicker">NeurIPS 2025 · Datasets & Benchmarks Track</span>
<h2 class="section-title">Poster</h2>
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<object data="static/pdfs/freshstack-poster.pptx.pdf" type="application/pdf">
<p>Your browser does not support PDFs. <a href="static/pdfs/freshstack-poster.pptx.pdf" download>Download the poster</a>.</p>
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<a class="button is-rounded is-dark" href="static/pdfs/freshstack-poster.pptx.pdf" download>
<span class="icon"><i class="fas fa-download"></i></span><span>Download poster (PDF)</span>
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</section>
<!--BibTex citation -->
<section class="section page-section is-tinted" id="BibTeX">
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<span class="section-kicker">Cite us</span>
<h2 class="section-title">BibTeX</h2>
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<pre id="bibtex-text"><code>@inproceedings{thakur2025freshstack,
title={FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents},
author={Nandan Thakur and Jimmy Lin and Sam Havens and Michael Carbin and Omar Khattab and Andrew Drozdov},
booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2025},
url={https://openreview.net/forum?id=54TTgXlS2U}
}</code></pre>
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</section>
<!--End BibTex citation -->
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