alabnii/sciclaimeval-shared-task huggingface dataset:
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\begin{document}
\begin{table}
\centering
\begin{adjustbox}{max width=\textwidth}
\begin{tabular}{llcccccccccccccc}
\toprule
&
\textbf{Model} &
\textbf{Quality} &
\textbf{Formality} &
\textbf{Win} &
\textbf{Win \& Tie} &
\\
&
&
(1-5)
&
(1-3)
&
(\%)
&
(\%)
\\
\midrule
$(1)$
&
NLLB-200
&
4.25{\color{gray!80}\scriptsize$\pm$0.75}
&
2.69{\color{gray!80}\scriptsize$\pm$0.46}
&
$-$
&
$-$
\\
$(2)$
&
CG (\texttt{multi}) formal
& 4.00{\color{gray!80}\scriptsize$\pm$0.79}
& 2.63{\color{gray!80}\scriptsize$\pm$0.48}
& 56.3
& 81.3
\\
$(3)$
&
CG (\texttt{multi}) inf.
& 4.44{\color{gray!80}\scriptsize$\pm$0.70}
& 2.38{\color{gray!80}\scriptsize$\pm$0.69}
& 62.5
& 93.8
\\
$(4)$
&
FT (\texttt{multi}) formal
&
4.31{\color{gray!80}\scriptsize$\pm$0.85}
&
2.63{\color{gray!80}\scriptsize$\pm$0.48}
&
43.8
&
68.8
\\
$(5)$
&
FT (\texttt{multi}) inf.
& 4.13{\color{gray!80}\scriptsize$\pm$1.05}
& 2.44{\color{gray!80}\scriptsize$\pm$0.49}
& 62.5
& 93.8
\\

\bottomrule
\end{tabular}
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\caption{Table 6: \label{tab:human_eval_bn}
Human evaluation on Bengali,
with quality on a 5-point scale$\uparrow$
and formality on a 3-point scale ($\uparrow$: formal) with {\color{gray!80}standard deviations}.
Last two columns show pairwise comparison of formality scores to baseline NLLB-200 given the same source sentences (winning: scoring more in the direction of the desired formality).}
\end{table}
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