Update abstract, add temporary bibtex and paper link

Author: PabloVD

index.html

@@ -193,16 +193,17 @@ <h1 class="title is-1 publication-title">The DENARIO project:<br> Modular Automa
 
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-                <!-- Arxiv PDF link -->
-                <!-- <span class="link-block">
-                  <a href="https://arxiv.org/pdf/<ARXIV PAPER ID>.pdf" target="_blank"
+                <!-- Paper -->
+                <span class="link-block">
+                  <a href="https://astropilot-ai.github.io/DenarioPaperPage/" target="_blank"
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+                      <!-- <i class="ai ai-arxiv"></i> -->
+                      <i class="fas fa-file"></i>
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-                    <span>Paper</span>
+                    <span>Paper (Coming soon!)</span>
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+                </span>
 
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@@ -219,7 +220,7 @@ <h1 class="title is-1 publication-title">The DENARIO project:<br> Modular Automa
                   <a href="https://denario.readthedocs.io/en/latest/" target="_blank"
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+                      <i class="fas fa-book"></i>
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@@ -236,16 +237,6 @@ <h1 class="title is-1 publication-title">The DENARIO project:<br> Modular Automa
                   </a>
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-                <!-- ArXiv abstract Link -->
-                <!-- <span class="link-block">
-                  <a href="https://arxiv.org/abs/<ARXIV PAPER ID>" target="_blank"
-                    class="external-link button is-normal is-rounded is-dark">
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@@ -280,20 +271,26 @@ <h2 class="subtitle has-text-centered">
           <h2 class="title is-3">Abstract</h2>
           <div class="content has-text-justified">
             <p>
-              We present DENARIO, an AI multi-agent framework designed to perform end-to-end scientific research.
-              DENARIO can generate ideas, develop research plans, write and execute code, make plots, and write a
-              scientific
-              paper. DENARIO is built as a modular system, and therefore, can perform either very specific tasks, such as generating an idea, or carrying out end-to-end scientific analysis using <a style="color: hsl(204, 86%, 53%)" href="https://github.com/CMBAgents/cmbagent">cmbagent</a> as a deep-research backend. In this work, we describe DENARIO and
-              its
-              modules in detail and illustrate its capabilities by showing several AI-generated papers generated by it. 
-              These papers
-              cover many scientific disciplines, such as biology, chemistry, medicine, machine learning, and astronomy.
-              We show
-              how DENARIO can generate paper by combining ideas from different scientific disciplines. We also
-              publicly release
-              the code associated with DENARIO at <a style="color: hsl(204, 86%, 53%)"
-                href="https://github.com/AstroPilot-AI/Denario">Github</a>. DENARIO
-              will be deployed on Hugging Face and Cloud upon release of the paper this September.
+              We present Denario, an AI multi-agent system designed to serve as a scientific research assistant. Denario
+              can perform many different tasks, such as generating ideas, checking the literature, developing research
+              plans, writing and executing code, making plots, and drafting and reviewing a scientific
+              paper. The system has a modular architecture, allowing it to handle specific tasks, such as generating an
+              idea, or carrying out end-to-end scientific analysis using <a style="color: hsl(204, 86%, 53%)"
+                href="https://github.com/CMBAgents/cmbagent">cmbagent</a> as a deep-research backend. In
+              this work, we describe Denario and its modules in detail and illustrate its capabilities by presenting
+              multiple AI-generated papers generated by it. These papers cover many scientific disciplines, such as
+              astrophysics, biology, biophysics, biomedical informatics, chemistry, material science, mathematical
+              physics, medicine, and planetary science. Denario can also perform research combining ideas from
+              different disciplines, and we illustrate it by showing a paper that applies methods from quantum physics
+              and machine learning with astrophysical data. We report the evaluations performed on these
+              papers by domain experts, who provided both numerical scores and qualitative feedback. We analyze these
+              results to highlight the strengths, weaknesses, and limitations of the current system. Finally,
+              we discuss the ethical implications of AI-driven research and reflect on how such technology relates to
+              the philosophy of science. We publicly release the code at <a style="color: hsl(204, 86%, 53%)"
+                href="https://github.com/AstroPilot-AI/Denario">Github</a>. A Denario demo can also be
+              run directly on the web at <a style="color: hsl(204, 86%, 53%)"
+                href="https://huggingface.co/spaces/astropilot-ai/Denario">HugginFace Spaces</a>, and the full app will
+              be deployed on the cloud.
             </p>
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@@ -321,7 +318,7 @@ <h2 class="title is-3 has-text-centered">End to End Research Demo</h2>
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@@ -482,12 +479,19 @@ <h3 class="title is-4">Physics</h3>
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   <!--BibTex citation -->
-  <!-- <section class="section" id="BibTeX">
+  <section class="section" id="BibTeX">
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       <h2 class="title">BibTeX</h2>
-      <pre><code>BibTex Code Here</code></pre>
+      <pre><code>@software{Denario,
+      author = {Denario Authors},
+      title = {The Denario Project: Modular Automation of Scientific
+      Research with Multi-Agent Systems},
+      month = {October},
+      year = {2025},
+      url = {https://astropilot-ai.github.io/DenarioPaperPage/}
+      }</code></pre>
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-  </section> -->
+  </section>
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