From f13caa55fb0e7dd3edb0c8eadc9a75086eb35296 Mon Sep 17 00:00:00 2001
From: Yen-Jen Wang <wangyenjen@berkeley.edu>
Date: Sun, 25 Aug 2024 10:30:07 -0700
Subject: [PATCH] Update README.md

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 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index a583bc9..716b3f0 100644
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@@ -42,8 +42,8 @@ Our simulator settings, particularly with Mujoco, are finely tuned to closely mi
 <a href="https://wangyenjen.github.io/">Yen-Jen Wang*</a>,
 Xiang Zhu*, Chengming Shi*, Yanjiang Guo, Yichen Liu,
 <a href="http://people.iiis.tsinghua.edu.cn/~jychen/">Jianyu Chen†</a>
-*: Equal contribution. Project Co-lead.
-†: Corresponding Author.
+
+*: Equal contribution. Project Co-lead., †: Corresponding Author.
 
 Denoising World Model Learning(DWL) presents an advanced sim-to-real framework that integrates state estimation and system identification. This dual-method approach ensures the robot's learning and adaptation are both practical and effective in real-world contexts.