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                     <td>Not scalable<br>High latency & memory cost</td>
                     <td class="timeline-reference">
                     <a href="https://proceedings.neurips.cc/paper_files/paper/2020/file/6b493230205f780e1bc26945df7481e5-Paper.pdf" target="_blank">
-                        Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W., Rocktäschel, T., Riedel, S., & Kiela, D. (2020). Retrieval‑augmented generation for knowledge‑intensive NLP tasks. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. T. Lin (Eds.), Advances in Neural Information Processing Systems, 33, 9459–9474. Curran Associates, Inc.
+                        📄Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W., Rocktäschel, T., Riedel, S., & Kiela, D. (2020). Retrieval‑augmented generation for knowledge‑intensive NLP tasks. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. T. Lin (Eds.), Advances in Neural Information Processing Systems, 33, 9459–9474. Curran Associates, Inc.
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                     <td>Approximate (not exact)</td>
                     <td class="timeline-reference">
                     <a href="https://simg.baai.ac.cn/paperfile/25a43194-c74c-4cd3-b60f-0a1f27f8b8af.pdf" target="_blank">
-                        Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
+                        📄Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
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@@ -590,7 +590,7 @@
                     <td>Requires tuning<br>Cluster-quality sensitive</td>
                     <td class="timeline-reference">
                     <a href="https://arxiv.org/pdf/1702.08734" target="_blank">
-                        Johnson, J., Douze, M., & Jégou, H. (2019). Billion‑scale similarity search with GPUs. IEEE Transactions on Big Data, 7(3), 535–547. https://doi.org/10.1109/TBDATA.2019.2921572
+                        📄Johnson, J., Douze, M., & Jégou, H. (2019). Billion‑scale similarity search with GPUs. IEEE Transactions on Big Data, 7(3), 535–547. https://doi.org/10.1109/TBDATA.2019.2921572
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@@ -605,7 +605,7 @@
                     <td>High memory usage<br>Complex construction</td>
                     <td class="timeline-reference">
                     <a href="https://arxiv.org/abs/1603.09320" target="_blank">
-                        Malkov, Y. A., & Yashunin, D. A. (2020). Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(4), 824–836. https://doi.org/10.1109/TPAMI.2018.2889473
+                        📄Malkov, Y. A., & Yashunin, D. A. (2020). Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(4), 824–836. https://doi.org/10.1109/TPAMI.2018.2889473
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                     <td>Lossy compression<br>Lower recall if misconfigured</td>
                     <td class="timeline-reference">
                     <a href="https://www.irisa.fr/texmex/people/jegou/papers/jegou_searching_with_quantization.pdf" target="_blank">
-                        Jégou, H., Douze, M., & Schmid, C. (2011). Product quantization for nearest neighbor search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(1), 117–128. https://doi.org/10.1109/TPAMI.2010.57
+                        📄Jégou, H., Douze, M., & Schmid, C. (2011). Product quantization for nearest neighbor search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(1), 117–128. https://doi.org/10.1109/TPAMI.2010.57
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                     <td>Not a full DBMS<br>Limited metadata</td>
                     <td class="timeline-reference">
                     <a href="https://simg.baai.ac.cn/paperfile/25a43194-c74c-4cd3-b60f-0a1f27f8b8af.pdf" target="_blank">
-                        Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
+                        📄Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
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@@ -662,7 +662,7 @@
                     <td>Deployment complexity<br>Operational overhead</td>
                     <td class="timeline-reference">
                     <a href="https://ijaibdcms.org/index.php/ijaibdcms/article/view/257?utm_source=chatgpt.com" target="_blank">
-                        Rusum, G. P., & Anasuri, S. (2025). Vector databases in modern applications: Real‑time search, recommendations, and retrieval‑augmented generation (RAG). International Journal of AI, BigData, Computational and Management Studies, 5(4), Article 113. https://doi.org/10.63282/3050‑9416.IJAIBDCMS‑V5I4P113
+                        📄Rusum, G. P., & Anasuri, S. (2025). Vector databases in modern applications: Real‑time search, recommendations, and retrieval‑augmented generation (RAG). International Journal of AI, BigData, Computational and Management Studies, 5(4), Article 113. https://doi.org/10.63282/3050‑9416.IJAIBDCMS‑V5I4P113
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@@ -675,7 +675,7 @@
                     <td>Closed-source<br>Opaque indexing</td>
                     <td class="timeline-reference">
                     <a href="https://simg.baai.ac.cn/paperfile/25a43194-c74c-4cd3-b60f-0a1f27f8b8af.pdf" target="_blank">
-                        Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
+                       📄Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
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@@ -688,7 +688,7 @@
                     <td>High memory usage<br>Limited ANN tuning</td>
                     <td class="timeline-reference">
                     <a href="https://ijaibdcms.org/index.php/ijaibdcms/article/view/257?utm_source=chatgpt.com" target="_blank">
-                        Rusum, G. P., & Anasuri, S. (2025). Vector databases in modern applications: Real‑time search, recommendations, and retrieval‑augmented generation (RAG). International Journal of AI, BigData, Computational and Management Studies, 5(4), Article 113. https://doi.org/10.63282/3050‑9416.IJAIBDCMS‑V5I4P113
+                      📄Rusum, G. P., & Anasuri, S. (2025). Vector databases in modern applications: Real‑time search, recommendations, and retrieval‑augmented generation (RAG). International Journal of AI, BigData, Computational and Management Studies, 5(4), Article 113. https://doi.org/10.63282/3050‑9416.IJAIBDCMS‑V5I4P113
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@@ -701,7 +701,7 @@
                     <td>Higher latency<br>Slower pure vector search</td>
                     <td class="timeline-reference">
                     <a href="https://simg.baai.ac.cn/paperfile/25a43194-c74c-4cd3-b60f-0a1f27f8b8af.pdf" target="_blank">
-                        Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
+                      📄Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
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@@ -714,7 +714,7 @@
                     <td>Limited scalability<br>Not enterprise-grade</td>
                     <td>
                     <a href="https://simg.baai.ac.cn/paperfile/25a43194-c74c-4cd3-b60f-0a1f27f8b8af.pdf" target="_blank">
-                        Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
+                       📄Gao, Y., Xiong, Y., Gao, X., Jia, K., Pan, J., Bi, Y., Dai, Y., Sun, J., Wang, M., & Wang, H. (2024). Retrieval‑Augmented Generation for Large Language Models: A Survey (arXiv:2312.10997). arXiv Preprint. https://doi.org/10.48550/arXiv.2312.10997
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