diff --git a/resources/views/manual/index.blade.php b/resources/views/manual/index.blade.php
index a56adbc118..897d33486c 100644
--- a/resources/views/manual/index.blade.php
+++ b/resources/views/manual/index.blade.php
@@ -312,6 +312,10 @@
                 <strong>Observations From Four Years of BIIGLE 2.0</strong><br>
                 <a href="https://doi.org/10.3389/fmars.2021.760036">Zurowietz, M., & Nattkemper, T. W. (2021). Current Trends and Future Directions of Large Scale Image and Video Annotation: Observations From Four Years of BIIGLE 2.0.</a><br>Frontiers in Marine Science, 8, 760036. doi: <code>10.3389/fmars.2021.760036</code>
             </p>
+            <p>
+                <strong>LabelBOT</strong><br>
+                <a href="https://doi.org/10.1109/ACCESS.2026.3688574">G. Kourie, M. Zurowietz, D. Langenkämper, D. Brembilla and T. W. Nattkemper, LabelBOT: A Human-in-the-Loop Classification Assistance in the BIIGLE Image Annotation Tool.</a> <br>IEEE Access, vol. 14, pp. 65161-65180, 2026. doi: <code>10.1109/ACCESS.2026.3688574</code>
+            </p>
             <p>
                 <strong>Video Object Tracking</strong><br>
                 <a href="https://doi.org/10.1109/CVPR.2017.515">Lukezic, A., Vojir, T., ˇCehovin Zajc, L., Matas, J., & Kristan, M. (2017). Discriminative correlation filter with channel and spatial reliability.</a> In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 6309-6318). doi: <code>10.1109/CVPR.2017.515</code>
diff --git a/resources/views/manual/tutorials/labelbot/labelbot.blade.php b/resources/views/manual/tutorials/labelbot/labelbot.blade.php
index 69ed14faca..f52fb156b1 100644
--- a/resources/views/manual/tutorials/labelbot/labelbot.blade.php
+++ b/resources/views/manual/tutorials/labelbot/labelbot.blade.php
@@ -9,7 +9,7 @@
         </p>
 
         <p>
-            LabelBOT is the automatic classification assistant of BIIGLE. It suggests labels for new annotations based on similar existing annotations, so you no longer have to select the labels yourself. This manual article explains how you can use LabelBOT and how it works under the hood.
+            LabelBOT <small class="text-muted"><a href="#ref1">[1]</a></small> is the automatic classification assistant of BIIGLE. It suggests labels for new annotations based on similar existing annotations, so you no longer have to select the labels yourself. This manual article explains how you can use LabelBOT and how it works under the hood.
         </p>
 
         <h3>How to use LabelBOT</h3>
@@ -63,5 +63,12 @@
         <p>
             Some part of the computation for LabelBOT is done in your browser. This can take several seconds on low-end or older machines. The computation will be dramatically faster if there is access to a dedicated graphics card via WebGPU. Access to WebGPU can also depend on the web browser and operating system. You can check <a href="https://webgpureport.org/">here</a> if WebGPU is available in your browser.
         </p>
+
+        <h3><a name="references"></a>References</h3>
+        <ol>
+            <li>
+                <a name="ref1"></a><a href="https://doi.org/10.1109/ACCESS.2026.3688574">G. Kourie, M. Zurowietz, D. Langenkämper, D. Brembilla and T. W. Nattkemper, LabelBOT: A Human-in-the-Loop Classification Assistance in the BIIGLE Image Annotation Tool.</a> In IEEE Access, vol. 14, pp. 65161-65180, 2026. doi: <code>10.1109/ACCESS.2026.3688574</code>
+            </li>
+        </ol>
     </div>
 @endsection