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diff --git a/docs/_build/html/_sources/guides/introduction.rst.txt b/docs/_build/html/_sources/guides/introduction.rst.txt
@@ -56,9 +56,7 @@ Regarding PiML high-code APIs, it is worthwhile to mention that these APIs are f
 
 Interpretable Models
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-PiML supports a growing list of inherently interpretable models. For simplicity, we only list the models and the references. The following list of interpretable models are included PiML toolbox V0.5 (latest update: May 4, 2023). 
-
-PiML supports a growing list of inherently interpretable models. For simplicity, we only list the models and the references. The following list of interpretable models are included PiML toolbox V0.5 (latest update: May 4, 2023). 
+PiML supports a growing list of inherently interpretable models. For simplicity, we only list the models and the references. The following list of interpretable models are included PiML toolbox V0.6 (latest update: Feb. 2024).
 
 - **GLM**: Linear/logistic regression with :math:`\ell_1` and/or :math:`\ell_2` regularization [Hastie2015]_
 

diff --git a/docs/_build/html/guides/introduction.html b/docs/_build/html/guides/introduction.html
@@ -247,8 +247,7 @@ <h2><span class="section-number">1.2. </span>Toolbox Design<a class="headerlink"
 </section>
 <section id="interpretable-models">
 <h2><span class="section-number">1.3. </span>Interpretable Models<a class="headerlink" href="#interpretable-models" title="Permalink to this heading">¶</a></h2>
-<p>PiML supports a growing list of inherently interpretable models. For simplicity, we only list the models and the references. The following list of interpretable models are included PiML toolbox V0.5 (latest update: May 4, 2023).</p>
-<p>PiML supports a growing list of inherently interpretable models. For simplicity, we only list the models and the references. The following list of interpretable models are included PiML toolbox V0.5 (latest update: May 4, 2023).</p>
+<p>PiML supports a growing list of inherently interpretable models. For simplicity, we only list the models and the references. The following list of interpretable models are included PiML toolbox V0.6 (latest update: Feb. 2024).</p>
 <ul class="simple">
 <li><p><strong>GLM</strong>: Linear/logistic regression with <span class="math notranslate nohighlight">\(\ell_1\)</span> and/or <span class="math notranslate nohighlight">\(\ell_2\)</span> regularization <a class="reference internal" href="#hastie2015" id="id19"><span>[Hastie2015]</span></a></p></li>
 <li><p><strong>GAM</strong>: Generalized additive models using B-splines <a class="reference internal" href="#serven2018" id="id20"><span>[Serven2018]</span></a></p></li>