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@@ -37,7 +37,7 @@ <h3><a href="#Education">Education and Experience</a> | <a href="#Publications">
 <h2><a id=News>News</a></h2>
 <li>Congratulations to Zhaoyang Yu et al. on our CCGRID 2024 paper! (Updated on 2024.02)</li>
 <li>Congratulations to Zexin Wang et al. on our WebConf 2024 paper!</li>
-<li>Congratulations to Zulong Diao et al. on our journal paper in TMC! (2023.11)</li>
+<li>Congratulations to Zulong Diao et al. on our journal paper in TMC! </li>
 <li>We are excited to announce the release of a benchmark designed to assess the performance of Large Language Models (LLMs) in the field of AIOps. For more details, please visit our website at https://opseval.cstcloud.cn/. </li>
 <li>Our ISSRE 2023 paper has just been awarded the Best Paper in the research track at the recently concluded ISSRE conference held in Italy. Congratulations to Zhaoyang Yu and his collaborators! </li>
 <li>Our ISSRE 2023 paper has been nominated as the best paper candidate, standing out as one of the top 3 among 247 submissions. </li>
@@ -71,7 +71,7 @@ <h3><strong>Preprints</strong></h3>
 	<li>Yuhe Liu, <b>Changhua Pei</b>, Longlong Xu, Bohan Chen, Mingze Sun, Zhirui Zhang, Yongqian Sun, Shenglin Zhang, Kun Wang, Haiming Zhang, Jianhui Li, Gaogang Xie, Xidao Wen, Xiaohui Nie, Dan Pei. <b>OpsEval: A Comprehensive Task-Oriented AIOps Benchmark for Large Language Models.</b> [<A HREF="https://arxiv.org/pdf/2310.07637.pdf" target=_blank><u>PDF</u></A>] [<A HREF="https://opseval.cstcloud.cn/content/leaderboard" target=_blank><u>BENCHMARK</u></A>]</li>
 
 <h3><strong>2024</strong></h3>
-	<li>Zhaoyang Yu, Qianyu Ouyang, <b>Changhua Pei</b>, Xin Wang, Wenxiao Chen, Liangfei Su, Huai Jiang, Xuanrun Wang, Jianhui Li, Dan Pei.Causality Enhanced Graph Representation Learning for Alert-Based Root Cause Analysis. The 24th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing. (CCGRID 2024)[<A HREF="https://arxiv.org/pdf/2402.02820.pdf" target=_blank><u>PDF</u></A>] [<A HREF="https://github.com/CSTCloudOps/FCVAE" target=_blank><u>CODES</u></A>]</li>
+	<li>Zhaoyang Yu, Qianyu Ouyang, <b>Changhua Pei</b>, Xin Wang, Wenxiao Chen, Liangfei Su, Huai Jiang, Xuanrun Wang, Jianhui Li, Dan Pei.Causality Enhanced Graph Representation Learning for Alert-Based Root Cause Analysis. The 24th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing. (CCGRID 2024)</li>
 	<li>Zexin Wang, <b>Changhua Pei</b>, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin, Haiming Zhang, Jianhui Li, Gaogang Xie. Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective. The World Wide Web Conference. (WWW 2024)[<A HREF="https://arxiv.org/pdf/2402.02820.pdf" target=_blank><u>PDF</u></A>] [<A HREF="https://github.com/CSTCloudOps/FCVAE" target=_blank><u>CODES</u></A>]</li>
 
 <h3><strong>2023</strong></h3>