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Manuscript revision and pending experiment work, snapshot before restructuring

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Clarity pass over the main text (36-item audit), Discussion rewrite and cut,
acknowledgements, Souly et al. as ref 62, lettered SI panels, model section
moved under Results; plus the untracked curriculum/society/compose/smol
configs, runners, figures, stats and tests that the SI already cites.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
This commit is contained in:
Giorgio Gilestro 2026-09-13 16:54:09 +01:00
parent e4804adabc
commit 84124de143
450 changed files with 52813 additions and 1202 deletions
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12
figures/plot_grounding.py
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@ -26,7 +26,7 @@ import matplotlib.pyplot as plt
import numpy as np
sys.path.insert(0, str(Path(__file__).parent))
from _figlib import load_bundle, mean_ci, savefig # noqa: E402
from _figlib import load_bundle, mean_ci, savefig, letter_axes # noqa: E402
sys.path.insert(0, str(Path(__file__).parents[1] / "src"))
from knowledge.analysis import reduce_to_stationary # noqa: E402
@ -94,8 +94,8 @@ def main(results_dir: str = "results/grounding") -> None:
ax.errorbar(kg, Km, yerr=Kci, fmt="o-", color="#1f77b4", capsize=3, zorder=3)
ax.set(xlabel="grounding fraction $g=m/(n+m)$",
ylabel=r"stationary forward-KL $D(p^*\Vert\hat p)$",
title="Neural phase boundary: KL falls monotonically\n"
"(sign confirmed; paired $t$=3.3 at g=0.2)")
title="Trained RNN: KL falls monotonically with grounding\n"
"(paired $t$=3.3 at $g$=0.2)")
# Panel C: recovery fraction with the median-recovery grounding vs Layer-1's g*.
ax = axes[1, 0]
@ -106,7 +106,7 @@ def main(results_dir: str = "results/grounding") -> None:
ax.axvspan(lo50, hi50, color="#d62728", alpha=0.15)
ax.axvline(g50, color="#d62728", lw=1.2,
label=f"median-recovery $g$={g50:.3f}\n(95% CI [{lo50:.3f},{hi50:.3f}])")
ax.axvline(_LAYER1_GSTAR, ls="--", color="k", lw=1, label=f"Layer-1 $g^*$={_LAYER1_GSTAR}")
ax.axvline(_LAYER1_GSTAR, ls="--", color="k", lw=1, label=f"analytic $g^*$={_LAYER1_GSTAR}")
ax.set(xlabel="grounding fraction $g$", ylabel="forward-KL recovery fraction",
title="Half the divergence gap closes by $g\\approx0.04$\n"
"(full recovery needs more g: smoothing softens the threshold)")
@ -131,10 +131,8 @@ def main(results_dir: str = "results/grounding") -> None:
"(smoothing keeps spurious support); forward-KL responds")
ax.legend(frameon=False, fontsize=8)
fig.suptitle("grounding — grounding arrests collapse in trained RNN weights (SIGN confirmed); "
f"the sharp $g^*\\ll1$ is carried by the histogram bridge ($g^*$=0.047, $H^*$={H_star:.2f})",
y=1.0, fontsize=12)
fig.tight_layout()
letter_axes(fig)
savefig(fig, results_dir, "grounding")