## 5 Experiments
### Experimental Results
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**Dataset** & **LLMs** & \begin{tabular}{c} **BERTScore** \\ **0\%** \\ \end{tabular} & \begin{tabular}{c} **BERTScore of SwapAlpha** \\ **20\%** \\ \end{tabular} & \
\begin{tabular}{c} **BERTScore of SwapWord** \\ **100\%** \\ \end{tabular} &
\begin{tabular}{c} **BERTScore of UpperCase** \\ **20\%** \\ \end{tabular} \\ \hline \multirow{3}{*}{MMLU} & GLM4 & \multirow{3}{*}{1.00} & \multirow{3}{*}{0.875} & \multirow{3}{*}{0.723} & \multirow{3}{*}{0.565} & \multirow{3}{*}{0.905} & \multirow{3}{*}{0.905} & \multirow{3}{*}{0.875} & \multirow{3}{*}{0.729} & \multirow{3}{*}{0.583} \\  & Llama3.1 & & & & & & & & & \\ \cline{1-1}  & Qwen2.5 & & & & & & & & & \\ \cline{1-1}  & Falcon3-Mamba & & & & & & & & & \\ \hline \multirow{3}{*}{LogiQA-en} & GLM4 & \multirow{3}{*}{1.00} & \multirow{3}{*}{0.858} & \multirow{3}{*}{0.698} & \multirow{3}{*}{0.522} & \multirow{3}{*}{0.885} & \multirow{3}{*}{0.885} & \multirow{3}{*}{0.885} & \multirow{3}{*}{0.685} & \multirow{3}{*}{0.696} & \multirow{3}{*}{0.525} \\  & Llama3.1 & & & & & & & & & \\ \cline{1-1}  & Qwen2.5 & & & & & & & & & \\ \cline{1-1}  & Falcon3-Mamba & & & & & & & & & \\ \hline \multirow{3}{*}{SAT-en} & GLM4 & \multirow{3}{*}{1.00} & \multirow{3}{*}{0.827} & \multirow{3}{*}{0.665} & \multirow{3}{*}{0.510} & \multirow{3}{*}{0.879} & \multirow{3}{*}{0.879} & \multirow{3}{*}{0.822} & \multirow{3}{*}{0.660} & \multirow{3}{*}{0.515} \\  & Llama3.1 & & & & & & & & & \\ \cline{1-1}  & Qwen2.5 & & & & & & & & & \\ \cline{1-1}  & Falcon3-Mamba & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Response BERTScore among different perturbations (SwapAlpha, SwapWord, CaseAlpha) of different levels (0%, 20%, 50%, 100%) across four datasets (MMLU, LogiQA-en, LSAT, and SAT-en) using four LLMs (GLM4, Llama3.1, Qwen2.5, and Falcon3-Mamba). \begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**Dataset** & **LLMs** & \begin{tabular}{c} **BLEU-1 Score** \\ **0\%** \\ \end{tabular} & \begin{tabular}{c} **BLEU-1 Score** \\ **20\%** \\ \end{tabular} & \begin{tabular}{c} **BLEU-1 Score of SwapAlpha** \\ **50\%** \\ \end{tabular} & \
\begin{tabular}{c} **BLEU-1 Score of SwapWord** \\ **100\%** \\ \end{tabular} &
\begin{tabular}{c} **BLEU-1 Score of UpperCase** \\ **20\%** \\ \end{tabular} \\ \hline \multirow{3}{*}{MMLU} & GLM4 & \multirow{3}{*}{1.00} & \multirow{3}{*}{0.834} & \multirow{3}{*}{0.557} & \multirow{3}{*}{0.086} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00} & \multirow{3}{*}{0.825} & \multirow{3}{*}{0.534} & \multirow{3}{*}{0.042} \\  & Llama3.1 & & & & & & & & & \\ \cline{1-1}  & Qwen2.5 & & & & & & & & & \\ \cline{1-1}  & Falcon3-Mamba & & & & & & & & & \\ \hline \multirow{3}{*}{LogiQA-en} & GLM4 & \multirow{3}{*}{1.00} & \multirow{3}{*}{0.821} & \multirow{3}{*}{0.542} & \multirow{3}{*}{0.079} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00} & \multirow{3}{*}{0.809} & \multirow{3}{*}{0.515} & \multirow{3}{*}{0.026} \\  & Llama3.1 & & & & & & & & & \\ \cline{1-1}  & Qwen2.5 & & & & & & & & & \\ \cline{1-1}  & Falcon3-Mamba & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Response BLEU-1 score among different perturbations (SwapAlpha, SwapWord, CaseAlpha) of different levels (0%, 20%, 50%, 100%) across four datasets (MMLU, LogiQA-en, LSAT, and SAT-en) using four LLMs (GLM4, Llama3.1, Qwen2.5, and Falcon3-Mamba). average decline in ACC under SwapWord perturbations, which is significantly smaller than the declines observed in other models, indicating that Falcon3-Mamba demonstrates exceptionally high robustness in this particular perturbation type. The consistent degradation of ACC across all models empirically validates that perturbations impair model performance by increasing the semantic divergence between input and output, making predictions increasingly error-prone without corrective mechanisms.