\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 / Development Set)} \\
\cline{2-8}
& Stereotype & Vilification & Dehumanization & Extreme Language & Lack of Empathy & Invalidation & Macro F1 \\
\hline
Gemma-3 (27B)             & 0.5247 & 0.6361 & 0.3831 & 0.4901 & 0.3927 & 0.4271 & 0.4723 \\ \hline
Mistral-small-3.2 (24B)   & 0.5127 & 0.5998 & 0.3125 & 0.4565 & 0.3606 & 0.3571 & 0.4332 \\ \hline
Phi-4 (14B)               & 0.5075 & 0.5729 & 0.2566 & 0.3891 & 0.3016 & 0.2629 & 0.3817 \\ \hline
Majority voting    & 0.5169 & 0.6261 & 0.3143 & 0.4280 & 0.3554 & 0.3273 & 0.4280 \\ \hline
Weighted voting    & 0.5410 & 0.6446 & 0.3833 & 0.5052 & 0.3704 & 0.4115 & 0.4760 \\ \hline
Stacking Ensemble         & \textbf{0.5564} & \textbf{0.6491} & \textbf{0.4568} & \textbf{0.5715} & \textbf{0.4190} & \textbf{0.4690} & \textbf{0.5203} \\ \hline
\end{tabular}}

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

\label{tab:subtask3_dev_18lang}
\end{table*}

