alabnii/sciclaimeval-shared-task huggingface dataset:
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\multirow{ 2}{*}{\textbf{Models}}& \multirow{ 2}{*}{\textbf{\underline{Red.}}} &\multicolumn{3}{c}{\textbf{\underline{Accuracy}}}\\
& &Avg.& Cal. \ding{55} & Cal. \ding{51}\\
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\multicolumn{5}{c}{\textit{Proprietary LLMs}} \\
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GPT-4& 11.7 &100.0$^\dagger$ & 100.0$^\dagger$ & 100.0$^\dagger$\\
ChatGPT& 47.1 &79.7& 96.6& 60.7\\
Claude-2& 74.7&88.4& 98.8& 84.8\\
PaLM & 29.2 &40.9& 40.9& 40.6\\
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\multicolumn{5}{c}{\textit{Open-source LLMs (Llama-2)}} \\
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70b-chat& 80.3 &54.5& 87.7& 46.3\\
13b-chat& 88.3 &39.9& 86.0& 33.8\\
7b-chat& 88.6 &41.4& 80.2& 36.3\\
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\caption{Table 1: The redundancy (\textbf{Red.}) and accuracy of LLMs' responses.
We report the average accuracy (\textbf{Avg.}) on all questions (second column), the accuracy for answers without calculation (Cal. \ding{55}, third column) and with calculation (Cal. \ding{51}, fourth column).
$\dagger$: The accuracy of GPT-4 is 100\% by construction since we use GPT-4 to filter samples when constructing GSM8K-Zero.}
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