RiteeshGrandhi/sciclaimeval-shared-task huggingface dataset:
\begin{table}
\centering
\begin{adjustbox}{max width=\textwidth}
\begin{tabular}{lllll}
\toprule
 & \multicolumn{2}{c}{\textbf{$\phi_{int}$}~(\%)} & \multicolumn{2}{c}{\textbf{$\phi_{p}$}~(\%)} \\
Method & \multicolumn{1}{c}{\textcolor{purple}{$r_s$}} & \multicolumn{1}{c|}{\textcolor{purple}{$r$}} & \teal{MiF1} & \teal{MaF1} \\ \midrule
Majority & - & \multicolumn{1}{c|}{-} & 43.41 & 20.18 \\
Random & 0.62 & \multicolumn{1}{c|}{0.41} & 35.51 & 30.55\\
ChatGPT & 43.80 & \multicolumn{1}{l|}{44.15} & 58.61 & 48.67 \\
DeBERTa & 50.81 & \multicolumn{1}{l|}{50.58} & 64.77 & 59.30 \\
RoBERTa & 52.09 & \multicolumn{1}{l|}{53.00} & 65.26 & 59.02 \\
InfoVGAE & 58.61 & \multicolumn{1}{l|}{58.37} & \textbf{68.45} & 60.05 \\
SocialSense & \textbf{61.82} & \multicolumn{1}{l|}{\textbf{61.98}} & 67.46 & \textbf{65.71} \\   \midrule
w/o belief & 59.92 & \multicolumn{1}{l|}{60.06} & 66.80 & 59.70 \\
w/o user-news & 55.43 & \multicolumn{1}{l|}{55.35} & 66.51 & 61.96 \\
w/o profile & 59.94 & \multicolumn{1}{l|}{60.01} & 64.49 & 59.04 \\
w/o history & 57.60 & \multicolumn{1}{l|}{57.29} & 67.95 & 62.89 \\
w/ random init & 58.25 & \multicolumn{1}{l|}{58.40} & 61.79 & 56.44 \\
 \bottomrule
\end{tabular}
\end{adjustbox}
\caption{Table 1: Response forecasting results. We report the Spearman and Pearson correlations for the forecasting of sentiment intensity, as well as Micro F1 and Macro F1 scores for the sentiment polarity prediction. The best overall performance is in bold. Our framework outperforms the baselines consistently.}
\end{table}