fix: unexcepted parse by ()

.github/workflows/update.yml

@@ -10,6 +10,7 @@ jobs:
     runs-on: ubuntu-latest
     env:
       TZ: "Asia/Shanghai"
+      UPTM: $(date "+%Y-%m-%d %H:%M:%S")
 
     steps:
       - name: Checkout
@@ -35,4 +36,4 @@ jobs:
       - name: Commit Updated
         uses: stefanzweifel/git-auto-commit-action@v4
         with:
-          commit_message: "auto update @ $(date '+%Y-%m-%d %H:%M:%S') ${{ env.TZ }}"
+          commit_message: "auto update @ ${{ env.UPTM }} ${{ env.TZ }}"

data.yaml

@@ -6285,7 +6285,7 @@ fl-in-top-db-conference-and-journal:
       top-K 草图（RTK-Sketch）的新结构，它显着加快了特征生成过程，同时保持了精度损失的理论保证。在公共数据集上进行的大量实验验证了所提出方法的有效性和效率。'
     materials:
       PUB: https://ieeexplore.ieee.org/document/9458704
-      RELATED PAPER(ZH): ZH
+      RELATED PAPER(ZH): https://kns.cnki.net/kcms/detail/detail.aspx?doi=10.13328/j.cnki.jos.006174
   - title: Feature Inference Attack on Model Predictions in Vertical Federated Learning
     affiliation: NUS
     venue: ICDE
@@ -7524,7 +7524,7 @@ federated-learning-framework:
     st: ':white_check_mark::white_check_mark:'
     materials:
       DOC: https://fate.readthedocs.io/en/latest/
-      DOC(ZH): ZH
+      DOC(ZH): https://fate.readthedocs.io/en/latest/zh/
   - platform: '[MindSpore Federated](https://github.com/mindspore-ai/mindspore/tree/master/tests/st/fl)<br
       />[![Stars](https://img.shields.io/github/stars/mindspore-ai/mindspore.svg?color=red)](https://github.com/mindspore-ai/mindspore/stargazers)<br
       />![](https://img.shields.io/github/last-commit/mindspore-ai/mindspore)'
@@ -7651,7 +7651,7 @@ federated-learning-framework:
     st: ''
     materials:
       DOC: https://fedlab.readthedocs.io/en/master/
-      DOC(ZH): ZH
+      DOC(ZH): https://fedlab.readthedocs.io/zh_CN/latest/
       PAGE: https://github.com/SMILELab-FL/FedLab-benchmarks
   - platform: '[Differentially Private Federated Learning: A Client-level Perspective](https://github.com/SAP-samples/machine-learning-diff-private-federated-learning)
       <br />[![Stars](https://img.shields.io/github/stars/SAP-samples/machine-learning-diff-private-federated-learning.svg?color=blue)](https://github.comSAP-samples/machine-learning-diff-private-federated-learning/stargazers)<br