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  <h1 class="title is-1 publication-title">CarBoN: Calibrated Best-of-N Sampling<br>Improves Test-time Reasoning</h1>
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  <div class="is-size-5 publication-authors">
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  <span class="author-block">
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- Yung-Chen Tang<sup>1,2</sup>,
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  </span>
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  <span class="author-block">
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- Pin-Yu Chen<sup>3</sup>,
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  </span>
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  <span class="author-block">
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- Andrea Cavallaro<sup>1,2</sup>
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  </span>
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  </div>
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  <div class="is-size-5 publication-authors">
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  <div class="publication-links">
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  <!-- arXiv Link. -->
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  <span class="link-block">
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- <a href="#"
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  class="external-link button is-normal is-rounded is-dark">
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  <span class="icon">
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  <i class="ai ai-arxiv"></i>
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  <section class="section" id="BibTeX">
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  <div class="container is-max-desktop content">
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  <h2 class="title">BibTeX</h2>
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- <pre><code>[Coming soon]</code></pre>
 
 
 
 
 
 
 
 
 
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  </div>
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  </section>
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  <h1 class="title is-1 publication-title">CarBoN: Calibrated Best-of-N Sampling<br>Improves Test-time Reasoning</h1>
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  <div class="is-size-5 publication-authors">
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  <span class="author-block">
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+ <a href="https://sites.google.com/view/yungchentang" target="_blank" rel="noopener noreferrer">Yung-Chen Tang</a><sup>1,2</sup>,
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  </span>
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  <span class="author-block">
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+ <a href="https://sites.google.com/site/pinyuchenpage/home" target="_blank" rel="noopener noreferrer">Pin-Yu Chen</a><sup>3</sup>,
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  </span>
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  <span class="author-block">
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+ <a href="https://people.epfl.ch/andrea.cavallaro?lang=en" target="_blank" rel="noopener noreferrer">Andrea Cavallaro</a><sup>1,2</sup>
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  </span>
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  </div>
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  <div class="is-size-5 publication-authors">
 
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  <div class="publication-links">
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  <!-- arXiv Link. -->
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  <span class="link-block">
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+ <a href="https://arxiv.org/abs/2510.15674" target="_blank" rel="noopener noreferrer"
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  class="external-link button is-normal is-rounded is-dark">
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  <span class="icon">
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  <i class="ai ai-arxiv"></i>
 
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  <section class="section" id="BibTeX">
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  <div class="container is-max-desktop content">
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  <h2 class="title">BibTeX</h2>
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+ <pre><code>@misc{tang2025carboncalibratedbestofnsampling,
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+ title={CarBoN: Calibrated Best-of-N Sampling Improves Test-time Reasoning},
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+ author={Yung-Chen Tang and Pin-Yu Chen and Andrea Cavallaro},
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+ year={2025},
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+ eprint={2510.15674},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.LG},
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+ url={https://arxiv.org/abs/2510.15674},
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+ }
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+ </code></pre>
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  </div>
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  </section>
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