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@@ -160,15 +160,15 @@ <h2>Publication</h2>
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       Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu, <strong>Ruiqi Zhang</strong>, Xiang Li, Bhiksha Raj, Huaxiu Yao
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-      <em>ICLR 2024 Workshop on Reliable and Responsible Foundation Models</em> | <a style="color: #447ec9" href="https://arxiv.org/abs/2402.11452">Paper</a>
+      <em>NAACL 2024</em> | <em>Prior version at ICLR 2024 Workshop on Reliable and Responsible Foundation Models</em> | <a style="color: #447ec9" href="https://arxiv.org/abs/2402.11452">Paper</a>
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       <li><strong>Trained Transformers Learn Linear Model In-Context.</strong>
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       <strong>Ruiqi Zhang</strong>, Spencer Frei, Peter L. Bartlett
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-      <em>Journal of Machine Learning Research (JMLR) 2024 25(49):1−55; Previous version in NIPS 2023 Workshop on robustness of zero/few-shot learning in foundation models (R0-FoMo)</em> | <a style="color: #447ec9" href="https://arxiv.org/abs/2306.09927">Paper (Arxiv)</a> | <a style="color: #447ec9" href="https://www.jmlr.org/papers/v25/23-1042.html">Paper (JMLR)</a>
+      <em>Journal of Machine Learning Research (JMLR) 2024 25(49):1−55 | Prior version in NIPS 2023 Workshop on robustness of zero/few-shot learning in foundation models (R0-FoMo)</em> | <a style="color: #447ec9" href="https://arxiv.org/abs/2306.09927">Paper (Arxiv)</a> | <a style="color: #447ec9" href="https://www.jmlr.org/papers/v25/23-1042.html">Paper (JMLR)</a>
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