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Deepseek paper listing.

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- content="Deformable Neural Radiance Fields creates free-viewpoint portraits (nerfies) from casually captured videos.">
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- <meta name="keywords" content="Nerfies, D-NeRF, NeRF">
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- <title>Nerfies: Deformable Neural Radiance Fields</title>
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  <div class="container is-max-desktop">
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- <h1 class="title is-1 publication-title">Nerfies: Deformable Neural Radiance Fields</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://keunhong.com" target="_blank">Keunhong Park</a><sup>1</sup>,</span>
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- <span class="author-block">
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- <a href="https://utkarshsinha.com" target="_blank">Utkarsh Sinha</a><sup>2</sup>,</span>
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- <span class="author-block">
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- <a href="https://jonbarron.info" target="_blank">Jonathan T. Barron</a><sup>2</sup>,
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- <a href="http://sofienbouaziz.com" target="_blank">Sofien Bouaziz</a><sup>2</sup>,
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- </span>
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- <span class="author-block">
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- <a href="https://www.danbgoldman.com" target="_blank">Dan B Goldman</a><sup>2</sup>,
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- </span>
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- <span class="author-block">
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- <a href="https://homes.cs.washington.edu/~seitz/" target="_blank">Steven M. Seitz</a><sup>1,2</sup>,
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- </span>
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- <span class="author-block">
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- <a href="http://www.ricardomartinbrualla.com" target="_blank">Ricardo Martin-Brualla</a><sup>2</sup>
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  <div class="is-size-5 publication-authors">
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- <span class="author-block"><sup>1</sup>University of Washington,</span>
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- <span class="author-block"><sup>2</sup>Google Research</span>
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  </div>
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- <div class="column has-text-centered">
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- <div class="publication-links">
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- <!-- PDF Link. -->
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- <span class="link-block">
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- <a href="https://arxiv.org/pdf/2011.12948" target="_blank"
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- <span class="icon">
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- <i class="fas fa-file-pdf"></i>
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- </span>
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- <span>Paper</span>
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- </a>
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- </span>
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- <a href="https://arxiv.org/abs/2011.12948" target="_blank"
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- <i class="ai ai-arxiv"></i>
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- <span>arXiv</span>
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- </a>
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- <span>Video</span>
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- <a href="https://github.com/google/nerfies" target="_blank"
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- <span>Code</span>
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- <a href="https://github.com/google/nerfies/releases/tag/0.1" target="_blank"
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- <span>Data</span>
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- </a>
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- <h2 class="subtitle has-text-centered">
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- <span class="dnerf">Nerfies</span> turns selfie videos from your phone into
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- free-viewpoint
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- portraits.
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- </h2>
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- </div>
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- <h2 class="title is-3">Abstract</h2>
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  <p>
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- We present the first method capable of photorealistically reconstructing a non-rigidly
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- deforming scene using photos/videos captured casually from mobile phones.
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- </p>
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- <p>
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- Our approach augments neural radiance fields
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- (NeRF) by optimizing an
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- additional continuous volumetric deformation field that warps each observed point into a
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- canonical 5D NeRF.
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- We observe that these NeRF-like deformation fields are prone to local minima, and
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- propose a coarse-to-fine optimization method for coordinate-based models that allows for
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- more robust optimization.
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- By adapting principles from geometry processing and physical simulation to NeRF-like
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- models, we propose an elastic regularization of the deformation field that further
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- improves robustness.
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- </p>
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- <p>
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- We show that <span class="dnerf">Nerfies</span> can turn casually captured selfie
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- photos/videos into deformable NeRF
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- models that allow for photorealistic renderings of the subject from arbitrary
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- viewpoints, which we dub <i>"nerfies"</i>. We evaluate our method by collecting data
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- using a
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- rig with two mobile phones that take time-synchronized photos, yielding train/validation
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- images of the same pose at different viewpoints. We show that our method faithfully
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- reconstructs non-rigidly deforming scenes and reproduces unseen views with high
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- fidelity.
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  </p>
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- <h2 class="title is-3">Video</h2>
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- <iframe src="https://www.youtube.com/embed/MrKrnHhk8IA?rel=0&amp;showinfo=0"
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- frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
 
 
 
 
 
 
 
 
 
 
 
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- <h2 class="title is-3">Visual Effects</h2>
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- <p>
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- Using <i>nerfies</i> you can create fun visual effects. This Dolly zoom effect
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- would be impossible without nerfies since it would require going through a wall.
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- </p>
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- <h2 class="title is-3">Matting</h2>
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- <p>
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- As a byproduct of our method, we can also solve the matting problem by ignoring
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- samples that fall outside of a bounding box during rendering.
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- <h2 class="title is-3">Animation</h2>
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- <h3 class="title is-4">Interpolating states</h3>
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- <p>
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- We can also animate the scene by interpolating the deformation latent codes of two input
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- frames. Use the slider here to linearly interpolate between the left frame and the right
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- frame.
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- </p>
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- <img src="./static/images/interpolate_start.jpg"
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- alt="Interpolate start reference image."/>
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- <p>Start Frame</p>
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- Loading...
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- alt="Interpolation end reference image."/>
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- <p class="is-bold">End Frame</p>
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- <br/>
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- <!--/ Interpolating. -->
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- <!-- Re-rendering. -->
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- <h3 class="title is-4">Re-rendering the input video</h3>
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- <div class="content has-text-justified">
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- <p>
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- Using <span class="dnerf">Nerfies</span>, you can re-render a video from a novel
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- viewpoint such as a stabilized camera by playing back the training deformations.
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- </p>
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- </div>
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- <div class="content has-text-centered">
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- <video id="replay-video"
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- controls
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- muted
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- playsinline
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- width="75%">
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- <source src="./static/videos/replay.mp4"
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- type="video/mp4">
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- </video>
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  </div>
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- <!--/ Re-rendering. -->
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-
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- </div>
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- </div>
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- <!--/ Animation. -->
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- <!-- Concurrent Work. -->
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- <div class="columns is-centered">
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- <div class="column is-full-width">
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- <h2 class="title is-3">Related Links</h2>
 
 
 
 
 
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- <div class="content has-text-justified">
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- <p>
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- There's a lot of excellent work that was introduced around the same time as ours.
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- </p>
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- <p>
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- <a href="https://arxiv.org/abs/2104.09125" target="_blank">Progressive Encoding for Neural Optimization</a> introduces an idea similar to our windowed position encoding for coarse-to-fine optimization.
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- </p>
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- <p>
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- <a href="https://www.albertpumarola.com/research/D-NeRF/index.html" target="_blank">D-NeRF</a> and <a href="https://gvv.mpi-inf.mpg.de/projects/nonrigid_nerf/" target="_blank">NR-NeRF</a>
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- both use deformation fields to model non-rigid scenes.
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- </p>
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- <p>
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- Some works model videos with a NeRF by directly modulating the density, such as <a href="https://video-nerf.github.io/" target="_blank">Video-NeRF</a>, <a href="https://www.cs.cornell.edu/~zl548/NSFF/" target="_blank">NSFF</a>, and <a href="https://neural-3d-video.github.io/" target="_blank">DyNeRF</a>
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- </p>
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- <p>
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- There are probably many more by the time you are reading this. Check out <a href="https://dellaert.github.io/NeRF/" target="_blank">Frank Dellart's survey on recent NeRF papers</a>, and <a href="https://github.com/yenchenlin/awesome-NeRF" target="_blank">Yen-Chen Lin's curated list of NeRF papers</a>.
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- </p>
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  </div>
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  </div>
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  </div>
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- <!--/ Concurrent Work. -->
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-
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  </div>
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  </section>
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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>@article{park2021nerfies,
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- author = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
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- title = {Nerfies: Deformable Neural Radiance Fields},
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- journal = {ICCV},
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- year = {2021},
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- }</code></pre>
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- </div>
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- </section>
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-
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  <footer class="footer">
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- This website is licensed under a <a rel="license" target="_blank"
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- This means you are free to borrow the <a target="_blank"
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- </html>
 
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  <html>
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  <head>
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  <meta charset="utf-8">
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+ <meta name="description" content="DeepSeek: Advancing Open-Source Language Models">
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+ <meta name="keywords" content="DeepSeek, LLM, AI">
 
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  <meta name="viewport" content="width=device-width, initial-scale=1">
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+ <title>DeepSeek: Advancing Open-Source Language Models</title>
 
 
 
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  <div class="container is-max-desktop">
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  <div class="columns is-centered">
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  <div class="column has-text-centered">
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+ <h1 class="title is-1 publication-title">DeepSeek: Advancing Open-Source Language Models</h1>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  <div class="is-size-5 publication-authors">
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+ A collection of groundbreaking research papers in AI and language models
 
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  </div>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  </div>
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  </div>
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  </div>
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  </section>
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  <section class="section">
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  <div class="container is-max-desktop">
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  <!-- Abstract. -->
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  <div class="columns is-centered has-text-centered">
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  <div class="column is-four-fifths">
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+ <h2 class="title is-3">Overview</h2>
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  <div class="content has-text-justified">
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  <p>
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+ DeepSeek has released a series of significant papers detailing advancements in large language models (LLMs).
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+ Each paper represents a step forward in making AI more capable, efficient, and accessible.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  </p>
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  </div>
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  </div>
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  </div>
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  <!--/ Abstract. -->
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+ <!-- Paper Collection -->
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  <div class="columns is-centered has-text-centered">
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  <div class="column is-four-fifths">
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+ <h2 class="title is-3">Research Papers</h2>
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+
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+ <!-- Paper 1 -->
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+ <div class="publication-block">
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+ <div class="publication-header">
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+ <h3 class="title is-4">DeepSeekLLM: Scaling Open-Source Language Models with Longer-termism</h3>
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+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
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+ <div class="is-size-5 publication-authors">
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+ Released: November 29, 2023
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+ </div>
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+ </div>
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+ <div class="content has-text-justified">
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+ <p>This foundational paper explores scaling laws and the trade-offs between data and model size,
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+ establishing the groundwork for subsequent models.</p>
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+ </div>
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  </div>
 
 
 
 
 
 
 
 
 
 
 
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+ <!-- Paper 2 -->
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+ <div class="publication-block">
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+ <div class="publication-header">
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+ <h3 class="title is-4">DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model</h3>
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+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
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+ <div class="is-size-5 publication-authors">
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+ Released: May 2024
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+ </div>
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+ </div>
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+ <div class="content has-text-justified">
88
+ <p>Introduces a Mixture-of-Experts (MoE) architecture, enhancing performance while reducing
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+ training costs by 42%.</p>
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+ </div>
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  </div>
 
 
92
 
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+ <!-- Additional papers following same structure -->
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+ <div class="publication-block">
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+ <div class="publication-header">
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+ <h3 class="title is-4">DeepSeek-V3 Technical Report</h3>
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+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
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+ <div class="is-size-5 publication-authors">
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+ Released: December 2024
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+ </div>
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+ </div>
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+ <div class="content has-text-justified">
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+ <p>Discusses the scaling of sparse MoE networks to 671 billion parameters.</p>
 
 
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  </div>
 
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  </div>
 
 
 
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+ <div class="publication-block">
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+ <div class="publication-header">
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+ <h3 class="title is-4">DeepSeek-R1: Incentivizing Reasoning Capability in LLMs</h3>
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+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
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+ <div class="is-size-5 publication-authors">
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+ Released: January 20, 2025
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  </div>
 
 
 
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  </div>
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+ <div class="content has-text-justified">
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+ <p>Enhances reasoning capabilities through large-scale reinforcement learning.</p>
 
 
 
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  </div>
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  </div>
 
 
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+ <div class="publication-block">
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+ <div class="publication-header">
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+ <h3 class="title is-4">DeepSeekMath: Pushing the Limits of Mathematical Reasoning</h3>
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+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
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+ <div class="is-size-5 publication-authors">
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+ Released: April 2024
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+ </div>
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+ </div>
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+ <div class="content has-text-justified">
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+ <p>Presents methods to improve mathematical reasoning in LLMs.</p>
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+ </div>
 
 
 
 
 
 
 
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  </div>
 
 
 
 
 
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+ <div class="publication-block">
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+ <div class="publication-header">
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+ <h3 class="title is-4">DeepSeek-Prover: Advancing Theorem Proving in LLMs</h3>
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+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
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+ </div>
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+ <div class="content has-text-justified">
139
+ <p>Focuses on enhancing theorem proving capabilities using synthetic data for training.</p>
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+ </div>
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+ </div>
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+ <div class="publication-block">
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+ <div class="publication-header">
145
+ <h3 class="title is-4">DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models</h3>
146
+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
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+ </div>
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+ <div class="content has-text-justified">
149
+ <p>Details advancements in code-related tasks with emphasis on open-source methodologies.</p>
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+ </div>
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+ </div>
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+ <div class="publication-block">
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+ <div class="publication-header">
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+ <h3 class="title is-4">DeepSeekMoE: Advancing Mixture-of-Experts Architecture</h3>
156
+ <span class="tag is-primary is-medium">Deep Dive Coming Soon</span>
157
+ </div>
158
+ <div class="content has-text-justified">
159
+ <p>Discusses the integration and benefits of the Mixture-of-Experts approach.</p>
160
+ </div>
 
 
 
 
 
 
 
 
 
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  </div>
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  </div>
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  </div>
 
 
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  </div>
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  </section>
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  <footer class="footer">
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  </a>
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+ This website is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative
 
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