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  1. app.py +5 -3
app.py CHANGED
@@ -104,7 +104,8 @@ We divided the 2,800 instances into three parts:
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  - train set: 20% of the data (covering all four datasets) was designated as the training set (including human annotations) for participants to reference when designing their methods.
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  - test set: Another 20% of the data was set aside as the test set (excluding human annotations), used to evaluate the performance of participants' methods and to generate the **leaderboard**.
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  - reserved set: The remaining 60% of the data was reserved for **the final evaluation**.
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- Both the training set and the test set can be downloaded from the provided link: [https://huggingface.co/datasets/THUIR/AEOLLM](https://huggingface.co/datasets/THUIR/AEOLLM)
 
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  """)
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  st.header("Resources")
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  st.markdown("""
@@ -120,8 +121,9 @@ elif page == "Important Dates":
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  st.markdown("""
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  <p class='main-text'><em class='main-text>All deadlines are at 11:59pm in the Anywhere on Earth (AOE) timezone.</em><br />
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  <span class='main-text'><strong>Kickoff Event</strong>:</span> <span class='main-text'>March 29, 2024</span><br />
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- <span class='main-text'><strong>Dataset Release</strong>:</span> <span class='main-text'>πŸ‘‰May 1, 2024</span><br />
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- <span class='main-text'><strong>System Output Submission Deadline</strong>:</span> <span class='main-text'>Jan 15, 2025</span><br />
 
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  <span class='main-text'><strong>Evaluation Results Release</strong>:</span> <span class='main-text'>Feb 1, 2025</span> <br />
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  <span class='main-text'><strong>Task overview release (draft)</strong>:</span> <span class='main-text'>Feb 1, 2025</span><br />
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  <span class='main-text'><strong>Submission Due of Participant Papers (draft)</strong>:</span> <span class='main-text'>March 1, 2025</span><br />
 
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  - train set: 20% of the data (covering all four datasets) was designated as the training set (including human annotations) for participants to reference when designing their methods.
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  - test set: Another 20% of the data was set aside as the test set (excluding human annotations), used to evaluate the performance of participants' methods and to generate the **leaderboard**.
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  - reserved set: The remaining 60% of the data was reserved for **the final evaluation**.
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+
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+ Both the training set and the test set can be downloaded from the provided link: [https://huggingface.co/datasets/THUIR/AEOLLM](https://huggingface.co/datasets/THUIR/AEOLLM).
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  """)
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  st.header("Resources")
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  st.markdown("""
 
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  st.markdown("""
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  <p class='main-text'><em class='main-text>All deadlines are at 11:59pm in the Anywhere on Earth (AOE) timezone.</em><br />
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  <span class='main-text'><strong>Kickoff Event</strong>:</span> <span class='main-text'>March 29, 2024</span><br />
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+ <span class='main-text'><strong>Dataset Release</strong>:</span> <span class='main-text'>May 1, 2024</span><br />
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+ <span class='main-text'><strong>Dry run Deadline</strong>:</span> <span class='main-text'>πŸ‘‰Jan 15, 2025</span><br />
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+ <span class='main-text'><strong>Formal run</strong>:</span> <span class='main-text'>Jan 15, 2025 - Feb 1, 2025</span> <br />
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  <span class='main-text'><strong>Evaluation Results Release</strong>:</span> <span class='main-text'>Feb 1, 2025</span> <br />
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  <span class='main-text'><strong>Task overview release (draft)</strong>:</span> <span class='main-text'>Feb 1, 2025</span><br />
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  <span class='main-text'><strong>Submission Due of Participant Papers (draft)</strong>:</span> <span class='main-text'>March 1, 2025</span><br />