diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index ecb8144..a095f9e 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -53,7 +53,10 @@ jobs:
         run: |
           git config --global user.name "github-actions"
           git config --global user.email "github-actions@github.com"
-          git add README.md paper_by_env paper_by_author update_template_or_data/statistics
+          git add README.md 
+          git add paper_by_env 
+          git add paper_by_author 
+          git add update_template_or_data/statistics
           git commit -m "Auto Updates"
           git push
         env:
diff --git a/update_template_or_data/update_paper_list.md b/update_template_or_data/update_paper_list.md
index b31dda7..ddd16fc 100644
--- a/update_template_or_data/update_paper_list.md
+++ b/update_template_or_data/update_paper_list.md
@@ -1,5 +1,12 @@
 
-
+- [Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents](https://arxiv.org/abs/2412.13194)
+  - Yifei Zhou, Qianlan Yang, Kaixiang Lin, Min Bai, Xiong Zhou, Yu-Xiong Wang, Sergey Levine, Erran Li
+  - 🏛️ Institutions: MSR, UIUC, Amazon
+  - 📅 Date: December 17, 2024
+  - 📑 Publisher: arXiv
+  - 💻 Env: [Web]
+  - 🔑 Key: [framework], [reinforcement learning], [skill discovery], [PAE]
+  - 📖 TLDR: This paper introduces the Proposer-Agent-Evaluator (PAE) system, enabling foundation model agents to autonomously discover and practice skills in real-world web environments. PAE comprises a context-aware task proposer, an agent policy for task execution, and a vision-language model-based success evaluator. Validated on vision-based web navigation tasks, PAE significantly enhances zero-shot generalization capabilities of vision-language model Internet agents, achieving over 30% relative improvement on unseen tasks and websites, and surpassing state-of-the-art open-source agents by more than 10%.
 
 - [UI Layout Generation with LLMs Guided by UI Grammar](https://arxiv.org/abs/2310.15455)
   - Yuwen Lu, Ziang Tong, Qinyi Zhao, Chengzhi Zhang, Toby Jia-Jun Li