陈俊杰
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9a958c5
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c3f31ee
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app.py
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@@ -124,7 +124,7 @@ st.markdown("""
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<style>
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/* 应用到所有的Markdown渲染文本 */
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.main-text {
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font-size:
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line-height: 1.6;
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color: #4CAF50;
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}
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elif page == "Evaluation Measures":
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st.header("Evaluation Measures")
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st.markdown("""
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<ul class='main-text'>
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<li><strong>Acc(Accuracy): </strong>The proportion of identical preference results between the model and human annotations. Specifically, we first convert individual scores (ranks) into pairwise preferences and then calculate consistency with human annotations.</li>
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<li><strong>Kendall's tau: </strong>Measures the ordinal association between two ranked variables. $$\tau = \frac{C-D}{\frac{1}{2}n(n-1)}$$
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# # 描述
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st.markdown("""
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<div class='main-text'>
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This leaderboard is used to show the performance of the
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<ul class='main-text'>
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<li>Dialogue Generation (DG)</li>
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<li>Text Expansion (TE)</li>
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<style>
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/* 应用到所有的Markdown渲染文本 */
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.main-text {
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font-size: 24px;
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line-height: 1.6;
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color: #4CAF50;
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}
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elif page == "Evaluation Measures":
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st.header("Evaluation Measures")
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st.markdown("""
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<script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
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<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
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<ul class='main-text'>
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<li><strong>Acc(Accuracy): </strong>The proportion of identical preference results between the model and human annotations. Specifically, we first convert individual scores (ranks) into pairwise preferences and then calculate consistency with human annotations.</li>
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<li><strong>Kendall's tau: </strong>Measures the ordinal association between two ranked variables. $$\tau = \frac{C-D}{\frac{1}{2}n(n-1)}$$
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# # 描述
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st.markdown("""
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<div class='main-text'>
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This leaderboard is used to show the performance of the <strong>automatic evaluation methods of LLMs</strong> submitted by the <strong>AEOLLM team</strong> on four tasks:
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<ul class='main-text'>
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<li>Dialogue Generation (DG)</li>
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<li>Text Expansion (TE)</li>
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