update authorship and pdf download

app/scripts/latex-importer/metadata-extractor.mjs

@@ -32,8 +32,11 @@ export function extractLatexMetadata(latexContent) {
         if (fullAuthorInfo.includes('\\ensps')) {
             affiliations.push(1); // École Normale Supérieure
         }
+        if (fullAuthorInfo.includes('\\oxford')) {
+            affiliations.push(1); // University of Oxford (index 1 dans le frontmatter)
+        }
         if (fullAuthorInfo.includes('\\hf')) {
-            affiliations.push(2); // Hugging Face
+            affiliations.push(2); // Hugging Face (index 2 dans le frontmatter)
         }
 
         // Clean author name by removing macros
@@ -58,15 +61,53 @@ export function extractLatexMetadata(latexContent) {
         metadata.authors = authors;
     }
 
-    // Extract affiliations - create the two distinct affiliations
-    metadata.affiliations = [
-        {
-            name: "École Normale Supérieure Paris-Saclay"
-        },
-        {
-            name: "Hugging Face"
+    // Extract affiliations dynamically from \contribution command
+    const contributionMatch = latexContent.match(/\\contribution\[\]\{([^}]+)\}/);
+    if (contributionMatch) {
+        const contributionText = contributionMatch[1];
+        
+        // Parse affiliations from contribution text
+        const affiliations = [];
+        
+        // Split by common separators and clean up
+        const parts = contributionText
+            .split(/[,;]/)
+            .map(part => part.trim())
+            .filter(part => part.length > 0);
+        
+        for (const part of parts) {
+            // Remove LaTeX commands and clean up
+            const cleanName = part
+                .replace(/\\[a-zA-Z]+/g, '')  // Remove LaTeX commands like \oxford, \hf
+                .replace(/\s+/g, ' ')         // Normalize whitespace
+                .trim();
+            
+            if (cleanName && cleanName.length > 0) {
+                affiliations.push({
+                    name: cleanName
+                });
+            }
         }
-    ];
+        
+        if (affiliations.length > 0) {
+            metadata.affiliations = affiliations;
+        }
+    }
+    
+    // Fallback to hardcoded affiliations if no \contribution found
+    if (!metadata.affiliations || metadata.affiliations.length === 0) {
+        metadata.affiliations = [
+            {
+                name: "École Normale Supérieure Paris-Saclay"
+            },
+            {
+                name: "University of Oxford"
+            },
+            {
+                name: "Hugging Face"
+            }
+        ];
+    }
 
     // Extract date if available (common LaTeX patterns)
     const datePatterns = [

app/scripts/latex-importer/output/main.mdx

@@ -2,7 +2,7 @@
 title: "Robot Learning: A Tutorial"
 authors:
   - name: "Francesco Capuano"
-    affiliations: [2]
+    affiliations: [1, 2]
   - name: "Caroline Pascal"
     affiliations: [2]
   - name: "Adil Zouitine"
@@ -12,9 +12,9 @@ authors:
   - name: "Michel Aractingi"
     affiliations: [2]
 affiliations:
-  - name: "École Normale Supérieure Paris-Saclay"
+  - name: "University of Oxford"
   - name: "Hugging Face"
-published: "Oct 14, 2025"
+published: "Oct 15, 2025"
 tableOfContentsAutoCollapse: true
 ---
 

app/src/components/Hero.astro

@@ -1,6 +1,7 @@
 ---
 import HtmlEmbed from "./HtmlEmbed.astro";
 import Image from "./Image.astro";
+import lerobotLogo from "../content/assets/image/figures/ch1/ch1-lerobot-figure1.png";
 
 interface Props {
   title: string; // may contain HTML (e.g., <br/>)
@@ -100,10 +101,14 @@ const pdfFilename = `${slugify(pdfBase)}.pdf`;
 
 <section class="hero">
   <h1 class="hero-title" set:html={title} />
-  <div class="hero-banner">
+  <!-- <div class="hero-banner">
     <HtmlEmbed src="banner.html" frameless />
+    <Image 
+      src={lerobotLogo} 
+      alt="LeRobot Logo" 
+    />
     {description && <p class="hero-desc">{description}</p>}
-  </div>
+  </div> -->
 </section>
 
 <header class="meta" aria-label="Article meta information">
@@ -209,9 +214,9 @@ const pdfFilename = `${slugify(pdfBase)}.pdf`;
         <p class="pdf-pro-only" style="display: none;">
           <a
             class="button"
-            href={`/${pdfFilename}`}
-            download={pdfFilename}
-            aria-label={`Download PDF ${pdfFilename}`}
+            href={`http://arxiv.org/pdf/2510.12403`}
+            target="_blank"
+            rel="noopener noreferrer"
           >
             Download PDF
           </a>
@@ -366,6 +371,14 @@ const pdfFilename = `${slugify(pdfBase)}.pdf`;
   .hero-banner {
     max-width: 980px;
     margin: 0 auto;
+    border: 1px solid var(--border-color);
+    border-radius: 8px;
+    margin-top: 8px;
+    margin-bottom: 8px;
+    overflow: hidden;
+  }
+  .hero-banner .ri-root {
+    border-radius: 8px;
   }
   .hero-desc {
     color: var(--muted-color);

app/src/content/article.mdx

@@ -2,7 +2,7 @@
 title: "Robot Learning: A Tutorial"
 authors:
   - name: "Francesco Capuano"
-    affiliations: [2]
+    affiliations: [1, 2]
   - name: "Caroline Pascal"
     affiliations: [2]
   - name: "Adil Zouitine"
@@ -12,9 +12,9 @@ authors:
   - name: "Michel Aractingi"
     affiliations: [2]
 affiliations:
-  - name: "École Normale Supérieure Paris-Saclay"
+  - name: "University of Oxford"
   - name: "Hugging Face"
-published: "Oct 14, 2025"
+published: "Oct 15, 2025"
 tableOfContentsAutoCollapse: true
 ---