## 5 Experiments
### Experimental Results
The plots demonstrate how the accuracy of the models changes across three perturbation types on four datasets. Each line in the chart represents the average performance decline of one model, with baseline performance (0% perturbation) normalized to 100%. The charts clearly show that Owen2.5 maintains relatively stable performance with minimal decline under SwapAlpha and CaseAlpha perturbations, suggesting its robustness to these types of perturbations. Conversely, Falcon3-Mamba exhibits the smallest decrease in performance under SwapWord perturbations, indicating its higher robustness in that specific perturbation type. These visual trends emphasize how different models react to various perturbations, with each model showing varying levels of sensitivity depending on the perturbation type, thereby highlighting the impact of the model architecture on its robustness. Figure 7 presents radar charts that provide a detailed comparison of the ACC of each LLM under various perturbation levels across different datasets. A larger radar chart area corresponds to higher overall ACC, indicating better model performance. It can be observed that the ACC of the four evaluated models exhibits a consistent trend: the radar chart areas decrease significantly as the perturbation levels increase. Among these models, \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Perturbation Type** & **Perturbation Level** & **Dataset** & **GLM4** & **Llama3.1** & **Owen2.5** & **Falcon3-Mamba** \\ \hline \multirow{8}{*}{SwapWord} & \multirow{8}{*}{20\%} & MMLU & \(-17.79\) & \(-16.07\) & \(-16.98\) & \(-17.06\) \\  & & LogiQA-en & \(-23.79\) & \(-15.19\) & \(-24.79\) & \(-10.69\) \\  & & LSAT & \(-28.57\) & \(-25.28\) & \(-27.03\) & \(-18.67\) \\  & & SAT-en & \(-17.78\) & \(-26.43\) & \(-19.49\) & \(-18.24\) \\ \cline{2-6}  & & Average & \(-21.98\) & \(-20.74\) & \(-22.07\) & \(-16.16\) \\ \cline{2-6}  & & MMLU & \(-23.19\) & \(-20.23\) & \(-20.73\) & \(-21.36\) \\  & & LogiQA-en & \(-33.07\) & \(-18.16\) & \(-28.00\) & \(-12.34\) \\  & & LSAT & \(-34.85\) & \(-31.54\) & \(-36.40\) & \(-24.84\) \\  & & SAT-en & \(-27.11\) & \(-38.75\) & \(-27.97\) & \(-25.55\) \\ \cline{2-6}  & & Average & \(-29.56\) & \(-27.17\) & \(-28.28\) & \(-21.02\) \\ \cline{2-6}  & & MMLU & \(-26.43\) & \(-23.14\) & \(-24.11\) & \(-23.51\) \\  & & LogiQA-en & \(-35.77\) & \(-28.21\) & \(-31.21\) & \(-13.45\) \\  & & LSAT & \(-41.87\) & \(-39.44\) & \(-40.64\) & \(-27.68\) \\  & & SAT-en & \(-34.11\) & \(-42.05\) & \(-31.63\) & \(-27.01\) \\ \cline{2-6}  & & Average & \(-34.54\) & \(-33.21\) & \(-31.90\) & \(-22.91\) \\ \cline{2-6}  & & Average & \(-28.69\) & \(-27.04\) & \(-27.42\) & \(-20.03\) \\ \hline \multirow{8}{*}{CaseAlpha} & \multirow{8}{*}{20\%} & MMLU & \(-1.78\) & \(-2.43\) & \(-1.09\) & \(-3.12\) \\  & & LogiQA-en & \(-3.18\) & \(-1.60\) & \(-1.54\) & \(-2.39\) \\  & & LSAT & \(-4.37\) & \(-4.86\) & \(-1.87\) & \(-0.64\) \\  & & SAT-en & \(-2.33\) & \(-5.11\) & \(-1.41\) & \(-2.18\) \\ \cline{2-6}  & & Average & \(-2.92\) & \(-3.50\) & \(-1.48\) & \(-2.08\) \\ \cline{2-6}  & & MMLU & \(-4.76\) & \(-6.30\) & \(-2.85\) & \(-5.77\) \\  & & LogiQA-en & \(-4.31\) & \(-4.94\) & \(-3.34\) & \(-4.23\) \\  & & LSAT & \(-6.65\) & \(-13.04\) & \(-5.21\) & \(-6.81\) \\  & & SAT-en & \(-2.62\) & \(-8.41\) & \(-3.11\) & \(-7.29\) \\ \cline{2-6}  & & Average & \(-4.58\) & \(-8.17\) & \(-3.63\) & \(-6.02\) \\ \hline \multirow{8}{*}{100\%} & \multirow{8}{*}{100\%} & MMLU & \(-9.21\) & \(-12.15\) & \(-5.39\) & \(-9.95\) \\  & & LogiQA-en & \(-11.18\) & \(-6.33\) & \(-8.08\) & \(-9.03\) \\ \cline{1-1}  & & LSAT & \(-13.64\) & \(-16.89\) & \(-11.32\) & \(-13.40\) \\ \cline{1-1}  & & SAT-en & \(-3.21\) & \(-24.34\) & \(-3.67\) & \(-10.21\) \\ \cline{1-1} \cline{2-6}  & & Average & \(-9.31\) & \(-14.93\) & \(-7.12\) & \(-10.65\) \\ \hline \multicolumn{2}{c}{Average} & \multicolumn{1}{c}{\(-\)**5.60**} & \(-\)**8.87** & \(-\)**4.07** & \(-\)**6.25** \\ \hline \hline \end{tabular}
\end{table}