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    <title>Diffusion on Tenu Tech Brief</title>
    <link>https://cluster-site.onrender.com/tags/diffusion/</link>
    <description>Recent content in Diffusion on Tenu Tech Brief</description>
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      <title>Conditional diffusion with locality-aware modal alignment for generating diverse protein conformational ensembles</title>
      <link>https://cluster-site.onrender.com/posts/conditional-diffusion-with-locality-aware-modal-alignment-for-generating-diverse-protein-conformational-ensembles/</link>
      <pubDate>Thu, 26 Feb 2026 07:32:53 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/conditional-diffusion-with-locality-aware-modal-alignment-for-generating-diverse-protein-conformational-ensembles/</guid>
      <description>• Abstract Recent advances in artificial intelligence have enabled accurate prediction of a protein&amp;rsquo;s stable structure solely based on its amino acid sequence • However, capturing</description>
    </item>
    <item>
      <title>Author Correction: Mask-prior-guided denoising diffusion improves inverse protein folding</title>
      <link>https://cluster-site.onrender.com/posts/author-correction-mask-prior-guided-denoising-diffusion-improves-inverse-protein-folding/</link>
      <pubDate>Wed, 25 Feb 2026 06:37:05 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/author-correction-mask-prior-guided-denoising-diffusion-improves-inverse-protein-folding/</guid>
      <description>• Subjects Computer science Machine learning Protein design TheOriginal Articlewas published on 16 June 2025 Correction to:Nature Machine Intelligencehttps://doi.org/10.1038/s42256</description>
    </item>
    <item>
      <title>Diffusion Modulation via Environment Mechanism Modeling for Planning</title>
      <link>https://cluster-site.onrender.com/posts/diffusion-modulation-via-environment-mechanism-modeling-for-planning/</link>
      <pubDate>Wed, 25 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/diffusion-modulation-via-environment-mechanism-modeling-for-planning/</guid>
      <description>• Computer Science &amp;gt; Artificial Intelligence [Submitted on 23 Feb 2026] Title:Diffusion Modulation via Environment Mechanism Modeling for Planning View PDF HTML (experimental)Abstr</description>
    </item>
    <item>
      <title>When Backdoors Go Beyond Triggers: Semantic Drift in Diffusion Models Under Encoder Attacks</title>
      <link>https://cluster-site.onrender.com/posts/when-backdoors-go-beyond-triggers-semantic-drift-in-diffusion-models-under-encoder-attacks/</link>
      <pubDate>Wed, 25 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/when-backdoors-go-beyond-triggers-semantic-drift-in-diffusion-models-under-encoder-attacks/</guid>
      <description>• Computer Science &amp;gt; Cryptography and Security [Submitted on 21 Feb 2026] Title:When Backdoors Go Beyond Triggers: Semantic Drift in Diffusion Models Under Encoder Attacks View PDF</description>
    </item>
    <item>
      <title>Who is using AI to code? Global diffusion and impact of generative AI</title>
      <link>https://cluster-site.onrender.com/posts/who-is-using-ai-to-code-global-diffusion-and-impact-of-generative-ai/</link>
      <pubDate>Tue, 24 Feb 2026 00:39:11 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/who-is-using-ai-to-code-global-diffusion-and-impact-of-generative-ai/</guid>
      <description>• Science, Volume 391, Issue 6787, Page 831-835, February 2026. • Science, Volume 391, Issue 6787, Page 831-835, February 2026.</description>
    </item>
    <item>
      <title>Overcoming Dimensional Factorization Limits in Discrete Diffusion Models through Quantum Joint Distribution Learning</title>
      <link>https://cluster-site.onrender.com/posts/overcoming-dimensional-factorization-limits-in-discrete-diffusion-models-through-quantum-joint-distribution-learning/</link>
      <pubDate>Tue, 24 Feb 2026 00:36:19 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/overcoming-dimensional-factorization-limits-in-discrete-diffusion-models-through-quantum-joint-distribution-learning/</guid>
      <description>• Abstract Discrete diffusion models typically rely on dimension-wise factorization to avoid computational intractability. • However, we rigorously prove this approach leads to wor</description>
    </item>
    <item>
      <title>Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies</title>
      <link>https://cluster-site.onrender.com/posts/diffusing-to-coordinate-efficient-online-multi-agent-diffusion-policies/</link>
      <pubDate>Mon, 23 Feb 2026 05:00:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/diffusing-to-coordinate-efficient-online-multi-agent-diffusion-policies/</guid>
      <description>• Computer Science &amp;gt; Artificial Intelligence [Submitted on 20 Feb 2026] Title:Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies View PDF HTML (experimental)A</description>
    </item>
    <item>
      <title>Language barriers slow down the international diffusion of knowledge, study finds</title>
      <link>https://cluster-site.onrender.com/posts/language-barriers-slow-down-the-international-diffusion-of-knowledge-study-finds/</link>
      <pubDate>Sun, 22 Feb 2026 19:10:01 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/language-barriers-slow-down-the-international-diffusion-of-knowledge-study-finds/</guid>
      <description>• Rapid technological and scientific advances have fueled a huge wave of innovation over the past decades. • The speed of global innovation is known to be dependent on the exchange</description>
    </item>
    <item>
      <title>Who is using AI to code? Global diffusion and impact of generative AI</title>
      <link>https://cluster-site.onrender.com/posts/who-is-using-ai-to-code-global-diffusion-and-impact-of-generative-ai/</link>
      <pubDate>Sun, 22 Feb 2026 00:39:30 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/who-is-using-ai-to-code-global-diffusion-and-impact-of-generative-ai/</guid>
      <description>• Science, Volume 391, Issue 6787, Page 831-835, February 2026.</description>
    </item>
    <item>
      <title>Overcoming Dimensional Factorization Limits in Discrete Diffusion Models through Quantum Joint Distribution Learning</title>
      <link>https://cluster-site.onrender.com/posts/overcoming-dimensional-factorization-limits-in-discrete-diffusion-models-through-quantum-joint-distribution-learning/</link>
      <pubDate>Sun, 22 Feb 2026 00:36:39 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/overcoming-dimensional-factorization-limits-in-discrete-diffusion-models-through-quantum-joint-distribution-learning/</guid>
      <description>• Abstract Discrete diffusion models typically rely on dimension-wise factorization to avoid computational intractability. • However, we rigorously prove this approach leads to wor</description>
    </item>
    <item>
      <title>Enhanced Li-ion diffusion improves N2-to-NH3 current efficiency at 100 mA cm−2</title>
      <link>https://cluster-site.onrender.com/posts/enhanced-li-ion-diffusion-improves-n2-to-nh3-current-efficiency-at-100-ma-cm2/</link>
      <pubDate>Thu, 19 Feb 2026 01:57:25 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/enhanced-li-ion-diffusion-improves-n2-to-nh3-current-efficiency-at-100-ma-cm2/</guid>
      <description>• Science, Volume 391, Issue 6786, Page 724-729, February 2026.</description>
    </item>
    <item>
      <title>Generating text with diffusion (and ROI with LLMs)</title>
      <link>https://cluster-site.onrender.com/posts/generating-text-with-diffusion-and-roi-with-llms/</link>
      <pubDate>Tue, 03 Feb 2026 08:40:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/generating-text-with-diffusion-and-roi-with-llms/</guid>
      <description>• In part 1, Ryan chats with the co-founder and CEO of Inception, Stefano Ermon, about diffusion language models and how their multiple token generation compares to traditional LLM</description>
    </item>
    <item>
      <title>Repurposing Protein Folding Models for Generation with Latent Diffusion</title>
      <link>https://cluster-site.onrender.com/posts/repurposing-protein-folding-models-for-generation-with-latent-diffusion/</link>
      <pubDate>Tue, 08 Apr 2025 10:30:00 +0000</pubDate>
      <guid>https://cluster-site.onrender.com/posts/repurposing-protein-folding-models-for-generation-with-latent-diffusion/</guid>
      <description>• PLAID is a multimodal generative model that simultaneously generates protein 1D sequence and 3D structure, by learning the latent space of protein folding models. • The awarding</description>
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