Match figure styling and labels to the submitted manuscript

Enlarge the in-canvas fonts and line weights of the result figures so
that they stay legible at the printed column width, split the Fig. 5
convergence curve into a pre-meta adaptation entry and the proposed
MAML entry, and rename the autoencoder legend to match the table row.
Add the analytic complexity replot behind Fig. 4, which was missing
from the repository, and correct the table numbering in the README.

c20_bert.py

@@ -441,7 +441,7 @@ def make_fig(args):
     LAB = {"digital_genie": "Digital chain genie CSI",
            "digital_pilot": "Digital chain pilot CSI",
            "semantic_tf": "Transformer SE separation",
-           "semantic_ae": "Per-user AE multiple access",
+           "semantic_ae": "Per-user AE",
            "semantic": "Proposed signed joint",
            "semantic_maml": "Proposed signed MAML"}
     STY = {"digital_genie": dict(color="gray", marker="^", ls="--"),
@@ -450,8 +450,14 @@ def make_fig(args):
            "semantic_ae": dict(color="tab:brown", marker="X", ls="-"),
            "semantic": dict(color="tab:red", marker="o", ls="-"),
            "semantic_maml": dict(color="tab:green", marker="D", ls="--")}
+    plt.rcParams.update({"font.size": 13, "axes.labelsize": 13,
+                         "xtick.labelsize": 12, "ytick.labelsize": 12,
+                         "axes.linewidth": 1.1, "grid.linewidth": 0.8,
+                         "xtick.major.width": 1.1, "ytick.major.width": 1.1,
+                         "xtick.minor.width": 0.8, "ytick.minor.width": 0.8,
+                         "xtick.major.size": 4.5, "ytick.major.size": 4.5})
     fig = plt.figure(figsize=(5.2, 3.9))
-    ax = fig.add_axes([0.14, 0.125, 0.835, 0.845])
+    ax = fig.add_axes([0.155, 0.145, 0.82, 0.82])
     for mkey in LAB:
         pts = sorted([(float(r["snr_db"]), float(r["ser"]))
                       for r in rows if r["method"] == mkey])
@@ -459,11 +465,12 @@ def make_fig(args):
         if not pts:
             continue
         xs, ys = zip(*pts)
-        ax.semilogy(xs, ys, label=LAB[mkey], ms=4, lw=1.3, **STY[mkey])
+        ax.semilogy(xs, ys, label=LAB[mkey], ms=5, lw=1.8, **STY[mkey])
     ax.set_xlabel("SNR (dB)")
     ax.set_ylabel("SER")
     ax.grid(True, which="both", alpha=0.35)
-    ax.legend(fontsize=7.5, loc="center right", bbox_to_anchor=(0.985, 0.66))
+    ax.legend(fontsize=9, framealpha=1.0, labelspacing=0.3,
+              handlelength=1.8, loc="center right", bbox_to_anchor=(0.985, 0.66))
     out = os.path.join(args.fig_dir,
                        f"bert_ser_vs_snr_fd{args.eval_fd}.pdf")
     fig.savefig(out)