Add new article: An Overview of Large Language Models for Statisticians

Author: dev-cla

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@@ -107,6 +107,29 @@ <h1 class="text-4xl font-bold mb-4">Latest Articles</h1>
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+      <article>
+          <time class="text-gray-500 dark:text-gray-400">April 9, 2025</time>
+          <h2 class="text-2xl font-bold mt-2 mb-3">
+            <a
+              href="an-overview-of-large-language-models-for-statisticians.html"
+              class="hover:text-primary dark:hover:text-turquoise"
+              >An Overview of Large Language Models for Statisticians</a
+            >
+          </h2>
+          <div class="flex flex-wrap gap-2 mb-3">
+          <span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Large Language Models</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">LLM</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Statistics</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Data Science</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">AI</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Machine Learning</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Transformers</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Pre-training</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Fine-tuning</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Interpretability</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Uncertainty Quantification</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Fairness</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Watermarking</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">Synthetic Data Generation</span><span class="text-xs text-primary bg-pink-50 px-2 py-1 rounded uppercase">LLM Alignment</span>
+          </div>
+          <p class="text-gray-600 dark:text-gray-400 mb-3">
+            Explore how statisticians can leverage and shape Large Language Models (LLMs) for trustworthy, fair, and efficient AI systems. Learn about interpretability, fine-tuning, uncertainty quantification, and alignment—plus how LLMs can revolutionize data science workflows.
+
+Large Language Models, LLM, Statistics, Data Science, Transformers, Fine-tuning, Interpretability, Alignment, Watermarking, Uncertainty Quantification, Fairness, Synthetic Data, Pre-training, AI, Machine Learning, Code Labs Academy
+          </p>
+          <a
+            href="an-overview-of-large-language-models-for-statisticians.html"
+            class="text-primary dark:text-blue-400 hover:text-pink-600 dark:hover:text-turquoise"
+            >Read more →</a
+          >
+        </article>
       <article>
           <time class="text-gray-500 dark:text-gray-400">April 8, 2025</time>
           <h2 class="text-2xl font-bold mt-2 mb-3">