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@@ -861,7 +861,7 @@ <h2 class="title is-3">Referances</h2>
         <li>LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., & Jackel, L. D. (1989). Backpropagation applied to handwritten zip code recognition. Neural Computation, 1(4), 541–551. <a href="https://doi.org/10.1162/neco.1989.1.4.541">https://doi.org/10.1162/neco.1989.1.4.541</a></li>
         <li>Hanson, S., & Pratt, L. (1988). Comparing biases for minimal network construction with backpropagation. Advances in Neural Information Processing Systems, 1.</li>
         <li>Hassibi, B., Stork, D. G., & Wolff, G. J. (1993, March). Optimal brain surgeon and general network pruning. In IEEE International Conference on Neural Networks, pp. 293–299. IEEE.</li>
-        <li>Lécuyer, M., McDaniel, P., & Papernot, N. (2019). Privacy-preserving and attack-resilient deep learning via compression. arXiv preprint arXiv:1902.00838.</li>
+        <li>Farhi, E., Goldstone, J., Gutmann, S., & Zhou, L. (2022). The quantum approximate optimization algorithm and the Sherrington-Kirkpatrick model at infinite size. Quantum, 6, 759.</li> <a href="https://doi.org/10.1038/nature14539">https://doi.org/10.1038/nature14539</a>
         <li>Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323(6088), 533–536. <a href="https://doi.org/10.1038/323533a0">https://doi.org/10.1038/323533a0</a></li>
         <li>Bengio, Y., LeCun, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. <a href="https://doi.org/10.1038/nature14539">https://doi.org/10.1038/nature14539</a></li>
         <li>Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press.</li>
@@ -885,13 +885,13 @@ <h2 class="title is-3">Referances</h2>
         <div class="content">
            <a href="https://github.com/edwardmagongo/QIANets-Website" target="_blank" style="display: inline-flex; align-items: center; margin: 0 10px;">
         <img src="Github Logo.jpg" alt="GitHub Logo" style="width: 42px; height: 42px; margin-right: 5px;"> 
-        <span>GitHub Code</span>
+        <span>Website Code</span>
     </a>
-<a href="https://arxiv.org/pdf/2410.10318v1" target="_blank" style="display: inline-flex; align-items: center; text-decoration: none;">
+<a href="https://thequantuminsider.com/2024/10/30/quantum-inspired-techniques-cut-latency-in-computer-vision-without-sacrificing-accuracy/" target="_blank" style="display: inline-flex; align-items: center; text-decoration: none;">
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         <i class="fas fa-file-pdf" style="font-size: 36px;"></i> <!-- Adjust the font size as needed -->
     </span>
-    <span style="margin-left: 5px;">Paper</span>
+    <span style="margin-left: 5px;">The Quantum Insider Article</span>
 </a>
         </div>
       </div>