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@@ -19,9 +19,9 @@ <h1>Hi, I'm Wang Shida(汪铈达).</h1>
               <a href="http://arxiv.org/abs/2311.14495v2">2. StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization (ICML 2024) </a><br>
               <a href="https://openreview.net/forum?id=i0OmcF14Kf">3. State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory (NeurIPS 2023) </a><br>
               &nbsp;&nbsp;&nbsp;&nbsp;<a href="https://github.com/radarFudan/Awesome-state-space-models">GitHub repo: Awesome-state-space-models </a><br>
-              <a href="https://arxiv.org/abs/2402.13297">4. Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-terminal Coding Sequences (Nature Computational Science) </a><br>
-              <a href="https://dl.acm.org/doi/10.1007/978-3-031-43415-0_9">5. Efficient Hyperdimensional Computing (ECML 2023) </a><br>
-              <a href="https://www.jml.pub/intro/article_detail/jml/21511.html">6. A Brief Survey on the Approximation Theory for Sequence Modelling (JML 2023)</a><br>
+              <a href="https://dl.acm.org/doi/10.1007/978-3-031-43415-0_9">4. Efficient Hyperdimensional Computing (ECML 2023) </a><br>
+              <a href="https://www.jml.pub/intro/article_detail/jml/21511.html">5. A Brief Survey on the Approximation Theory for Sequence Modelling (JML 2023)</a><br>
+              <a href="https://arxiv.org/abs/2402.13297">6. Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-terminal Coding Sequences (Nature Computational Science) </a><br>
        </p>
 
        <p><em>Manuscripts</em>: <br>