remove breadcrumbs

Author: RSTZZZ

_layouts/splash_v2.html

@@ -34,24 +34,24 @@
 </script>
 
 <div id="main" role="main">
-    <article class="splash" itemscope itemtype="https://schema.org/CreativeWork">
-        {% if page.title %}
-        <meta itemprop="headline" content="{{ page.title | markdownify | strip_html | strip_newlines | escape_once }}">
-        {% endif %}
-        {% if page.excerpt %}
-        <meta itemprop="description"
-            content="{{ page.excerpt | markdownify | strip_html | strip_newlines | escape_once }}">{% endif %}
-        {% if page.date %}
-        <meta itemprop="datePublished" content="{{ page.date | date_to_xmlschema }}">{% endif %}
-        {% if page.last_modified_at %}
-        <meta itemprop="dateModified" content="{{ page.last_modified_at | date_to_xmlschema }}">{% endif %}
+  <article class="splash" itemscope itemtype="https://schema.org/CreativeWork">
+    {% if page.title %}
+    <meta itemprop="headline" content="{{ page.title | markdownify | strip_html | strip_newlines | escape_once }}">
+    {% endif %}
+    {% if page.excerpt %}
+    <meta itemprop="description" content="{{ page.excerpt | markdownify | strip_html | strip_newlines | escape_once }}">
+    {% endif %}
+    {% if page.date %}
+    <meta itemprop="datePublished" content="{{ page.date | date_to_xmlschema }}">{% endif %}
+    {% if page.last_modified_at %}
+    <meta itemprop="dateModified" content="{{ page.last_modified_at | date_to_xmlschema }}">{% endif %}
 
 
-        {{ content }}
+    {{ content }}
 
-        <div>
-            {% include posts-publication.html taxonomy=page.taxonomy %}
-        </div>
+    <div>
+      {% include posts-publication.html taxonomy=page.taxonomy %}
+    </div>
 
-    </article>
+  </article>
 </div>

_research_directions/online-toxicity.md

@@ -20,8 +20,6 @@ logos:
     name: Mitacs
 ---
 
-{% include breadcrumbs.html %}
-
 Toxic and harmful speech online is more than just unpleasant; it has widespread social and economic repercussions, particularly as it permeates social media and gaming platforms. In gaming, where toxicity affects 75% of young players, this behavior harms mental health, alienates communities, and even reduces player engagement and spending, which impacts the industry’s bottom line. Beyond financial losses, unchecked toxicity risks fostering real-world violence and inciting harmful social behaviors. Despite advances in detection methods, including AI-driven moderation, the ever-evolving nature of toxic language poses significant challenges to companies and communities alike. Addressing this problem isn’t just about improving user experience — it’s essential for maintaining safe, inclusive, and healthy online spaces.
 
 

_research_directions/temporal-graph-learning.md

@@ -21,7 +21,6 @@ logos:
 
 ---
 
-{% include breadcrumbs.html %}
 
 Time-evolving graphs, also known as temporal networks, are a crucial area of study in network science and are ubiquitous in the real world. They represent systems where entities (nodes) and their interactions (edges) change over time. Understanding and predicting the behavior of these dynamic networks are essential for various applications, from tracking disease spread to detecting fraudulent activities and enhancing recommendation systems. However, modeling and analyzing time-evolving graphs presents significant challenges due to their complex and ever-changing nature. Therefore, there is a pressing need to develop advanced machine learning techniques that can effectively handle the unique characteristics of temporal networks.