update new paper

paper.md

@@ -671,6 +671,33 @@ Table: Summary of benchmark metrics (three independent seeds).
 ![Benchmark overview figure (workflow, feature fidelity, dataset shift, and robustness).](figures/benchmark_panel.svg)
 Benchmark 综合图（流程、特征级分布保真、训练集分布漂移与跨种子鲁棒性）。
 
+![Seed robustness summary across three independent runs.](figures/benchmark_metrics.svg)
+跨三次独立运行的鲁棒性汇总图。
+
+![KS outlier attribution (top-K features and average KS after removing worst features).](figures/ranked_ks.svg)
+KS 离群归因图（Top-K 误差特征与“移除最差特征后”的平均 KS 变化）。
+
+![CDF alignment for a representative set of high-KS continuous features: P1_B4002, P1_PIT02, P1_FCV02Z, P1_B3004.](example/results/cdf_P1_B4002.svg)
+代表性高 KS 连续特征的 CDF 对齐：P1_B4002。
+
+![CDF alignment for P1_PIT02.](example/results/cdf_P1_PIT02.svg)
+P1_PIT02 的 CDF 对齐图。
+
+![CDF alignment for P1_FCV02Z.](example/results/cdf_P1_FCV02Z.svg)
+P1_FCV02Z 的 CDF 对齐图。
+
+![CDF alignment for P1_B3004.](example/results/cdf_P1_B3004.svg)
+P1_B3004 的 CDF 对齐图。
+
+![All continuous features’ distribution comparison (empirical CDF grid: generated vs real).](figures/cdf_grid.svg)
+所有连续特征的分布对比（经验 CDF 网格：生成 vs 原始）。
+
+![Discrete features’ categorical distribution comparison (dot plot: generated vs real).](figures/disc_points.svg)
+离散特征的类别分布对比（点图：两种颜色分别代表生成与原始）。
+
+![Generated line series (normalized by real min/max) for four representative features: P1_B4002, P1_PIT02, P1_FCV02Z, P1_B3004.](figures/lines.svg)
+四个代表性特征的生成序列折线图（按真实 min/max 归一化）。
+
 Why this benchmark highlights where the method helps
 To make the benchmark actionable (and comparable to prior work), we report type-appropriate, interpretable statistics instead of collapsing everything into a single similarity score. This matters in mixed-type ICS telemetry: continuous fidelity can be high while discrete semantics fail, and vice versa. By separating continuous (KS), discrete (JSD), and temporal (lag-1) views, the evaluation directly matches the design goals of the hybrid generator: distributional refinement for continuous residuals, vocabulary-valid reconstruction for discrete supervision, and trend-induced short-horizon coherence.
 为何该基准测试能够凸显方法优势