\begin{table*}[t] % 跨雙欄
\centering
\renewcommand{\arraystretch}{1.10}
\setlength{\tabcolsep}{3pt}

\resizebox{\textwidth}{!}{%
\begin{tabular}{|c|c|c|c|c|c|c|c|}
\hline % 畫一條水平線
\multirow{2}{*}{Model (\#para)} &
\multicolumn{7}{c|}{Subtask 3: Polarization Manifestation Identification (18 Languages / Test Set)} \\
\cline{2-8}
& Stereotype & Vilification & Dehumanization & Extreme Language & Lack of Empathy & Invalidation & Macro F1 \\
\hline
Gemma-3 (27B)             & 0.5376 & 0.6117 & 0.3712 & 0.4916 & 0.3650 & 0.3689 & 0.4577 \\ \hline
Mistral-small-3.2 (24B)   & 0.5179 & 0.5883 & 0.3184 & 0.4567 & 0.3304 & 0.3317 & 0.4239 \\ \hline
Phi-4 (14B)               & 0.4842 & 0.5646 & 0.2752 & 0.3929 & 0.2705 & 0.2680 & 0.3759 \\ \hline
Stacking Ensemble         & \textbf{0.5586} & \textbf{0.6281} & \textbf{0.4516} & \textbf{0.5669} & \textbf{0.4255} & \textbf{0.4359} & \textbf{0.5111} \\ \hline
\end{tabular}}

\caption{Fine-tuned SLM results on the test set of Subtask 3. Each label score and Macro F1 are macro-F1 averaged over 18 languages.}

\label{tab:subtask3_test_18lang}
\end{table*}

